56 Data Scientists jobs in Houston

**JOB SUMMARY - Lead Data Engineer**
A Lead Data Engineer collaborates with the Data Quality and Governance team to ensure data pipelines, data integrity, and compliance by defining data strategies, implementing Data Governance capabilities, creating self-service data assets, and integrating robust data quality and governance frameworks to support trustworthy AI solutions. Key responsibilities include designing scalable data architectures, establishing data quality standards and monitoring, managing data lineage, and ensuring adherence to regulatory requirements and privacy policies
**KNOWLEDGE, SKILLS & ABILITIES** (Occupational knowledge and specific technical and professional skills and abilities required to perform the essential duties of this job):
**1. Data Quality & Governance Leadership**
+ Define and enforce data quality standards, validation rules, and monitoring systems tailored to healthcare data.
+ Collaborate with data stewards, compliance officers, and business stakeholders to resolve data integrity issues and ensure consistent data across systems.
+ Develop and maintain metadata management, data dictionaries, and stewardship workflows.
**2. Regulatory Compliance & Security**
+ Ensure all data engineering practices align with healthcare regulations such as HIPAA, HITECH, and other privacy laws.
+ Implement data governance policies that support secure, ethical, and compliant data usage across the organization.
**3. Data Architecture & Lifecycle Management**
+ Design scalable data architectures that support healthcare analytics and AI/ML workflows.
+ Automate data lineage tracking, governance documentation, and audit trails to support transparency and traceability.
+ Establish data lifecycle policies for retention, archiving, and disposal in accordance with regulatory and operational requirements.
**5. AI/ML Enablement**
+ Collaborate with data scientists and ML engineers to ensure data pipelines meet model training and inference requirements.
+ Architect and implement end-to-end AI pipelines using Agentic AI and GenAI frameworks.
+ Support the development of trustworthy AI by ensuring the use of reliable, consented, and well-governed data to ensure AI enabled solutions around Data Governance.
**6. Cross-Functional Collaboration**
+ Partner with clinical informatics, compliance, IT, and analytics teams to align data engineering efforts with healthcare delivery goals and governance strategies.
**7. Lead by example**
+ Must be hands on Data quality, Data Governance tools, Databricks, Power BI
+ Experience in Azure Data Services (like Azure Databricks, Unity Catalog, Purview, Azure Data Factory) and Power BI
+ Ability to lead, in solving technical issues while engaged with infrastructure and vendor support teams
+ Analyze current business practices, processes and procedures and identify opportunities for leveraging Microsoft Azure data & analytics PaaS services.
**8. Leadership & Mentorship**
+ Lead and mentor a team of data engineers, fostering a culture of quality, compliance, and innovation.
+ Oversee project delivery and ensure alignment with enterprise data governance objectives.
**JOB FUNCTION:**
Responsible for all the aspects of architecture, design and implementation of Data Governance in Databricks
**REQUIRED EDUCATION:**
Bachelor's Degree
**REQUIRED EXPERIENCE:**
+ 8 + years of data management experience
+ Prior experience leading projects or teams
+ Strong experience on Data Lake, Data Warehouse, Data Validation & Certification, Data Quality, Metadata Management and Data Governance
+ Experience in Azure Data Services (like Azure Databricks, Unity Catalog, Purview, Azure Data Factory) and Power BI, and in programming languages such as, PySpark/Python/SQL, etc.
+ Preferred experience in building stream-processing systems, using solutions such as Kafka, Storm or Spark-Streaming
+ Experience in implementing AI based solutions in Data Governance space
**PREFERRED EDUCATION:**
Master's Degree
**PREFERRED EXPERIENCE:**
Experience in the healthcare industry is preferred
To all current Molina employees: If you are interested in applying for this position, please apply through the intranet job listing.
Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.
Pay Range: $107,028 - $208,446 / ANNUAL
*Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.

Our client is seeking a highly skilled Senior Data Scientist with expertise in Machine Learning Engineering to join their growing IT & Software division in **Houston, Texas, US**. This role will be at the forefront of developing and deploying sophisticated machine learning models to solve complex business problems. You will work with large datasets, design and implement ML pipelines, and collaborate with software engineers to integrate models into production systems. The ideal candidate will have a strong theoretical foundation in machine learning and practical experience in applying ML techniques to real-world challenges. This hybrid position offers a collaborative environment with opportunities for both remote work and in-office interaction.

Key Responsibilities:

• Design, develop, and deploy machine learning models and algorithms to address business needs.
• Clean, preprocess, and analyze large, complex datasets to extract meaningful insights.
• Build and maintain scalable machine learning pipelines for model training, evaluation, and deployment.
• Collaborate with software engineers to integrate ML models into production applications and systems.
• Conduct A/B testing and other experiments to evaluate model performance and business impact.
• Stay current with the latest advancements in machine learning, artificial intelligence, and data science.
• Communicate complex technical findings and recommendations to both technical and non-technical stakeholders.
• Develop and implement strategies for model monitoring, retraining, and lifecycle management.
• Contribute to the development of data governance and best practices.
• Mentor junior data scientists and engineers, fostering a culture of innovation and knowledge sharing.

Qualifications:

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 6 years of experience in data science and machine learning, with a focus on ML engineering.
• Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Deep understanding of various machine learning algorithms, including supervised and unsupervised learning, deep learning, and natural language processing (NLP).
• Proven experience in building and deploying ML models into production environments.
• Experience with MLOps practices and tools (e.g., MLflow, Kubeflow).
• Excellent problem-solving, analytical, and critical-thinking skills.
• Strong communication and collaboration skills, with the ability to work effectively in a hybrid team setting.

This hybrid role offers a competitive salary, comprehensive benefits, and the chance to work on impactful data science projects in **Houston, Texas, US**. Join a team pushing the boundaries of AI and machine learning.

Our client is seeking a highly motivated and intellectually curious Graduate Data Scientist with a strong interest in Machine Learning to join their team. This hybrid role offers a blend of remote work flexibility and essential in-office collaboration, providing a comprehensive learning and development experience. You will work closely with experienced data scientists and engineers to apply advanced statistical and machine learning techniques to solve complex business problems. Your responsibilities will include data collection, cleaning, preprocessing, feature engineering, and building predictive models. You will gain hands-on experience with various machine learning algorithms, deep learning frameworks, and data visualization tools. The ideal candidate possesses a solid foundation in mathematics, statistics, computer science, and a demonstrated passion for machine learning. Proficiency in programming languages such as Python or R, along with experience using libraries like TensorFlow, PyTorch, scikit-learn, and Pandas, is required. You will have the opportunity to contribute to real-world projects, analyze large datasets, and help drive data-informed decision-making across the organization. Excellent analytical, problem-solving, and communication skills are essential. This internship is designed for individuals who are eager to learn, grow, and make a meaningful contribution. Our client is committed to fostering a supportive and collaborative environment where interns can develop their skills and gain valuable industry experience. This role requires a commitment to both remote work and regular attendance in the office to foster team integration and mentorship.

Responsibilities:

• Assist in data collection, cleaning, and preprocessing from various sources.
• Develop and implement machine learning models for predictive analysis and classification.
• Perform exploratory data analysis (EDA) to uncover insights and patterns.
• Create data visualizations to communicate findings effectively.
• Collaborate with senior data scientists on model evaluation and refinement.
• Participate in defining project requirements and data needs.
• Learn and apply new data science techniques and tools.
• Document methodologies, code, and results clearly.
• Contribute to team discussions and present findings.
• Support A/B testing and experiment design.

This hybrid internship offers a fantastic opportunity for an aspiring data scientist to gain practical experience in a dynamic industry. The exposure to cutting-edge machine learning applications and the mentorship provided will be invaluable for career development. The role supports various business units, with a primary focus on contributing to projects within the energy sector in the Houston, Texas, US area, while also leveraging remote collaboration tools.

Our client is seeking an innovative and experienced Lead Data Scientist to spearhead their AI and Machine Learning initiatives. This is a fully remote position, allowing you to contribute your expertise from anywhere within the US. You will be responsible for designing, developing, and deploying sophisticated machine learning models that drive business growth and enhance product capabilities. This role involves working with large, complex datasets, identifying patterns, and extracting actionable insights to solve challenging business problems across various domains. As a Lead Data Scientist, you will mentor a team of talented data scientists, guide their technical development, and oversee project execution from conception to deployment. Your responsibilities will include defining data science roadmaps, selecting appropriate algorithms and tools, conducting rigorous model evaluation, and ensuring the scalability and reliability of deployed solutions. Strong proficiency in programming languages such as Python or R, along with experience in deep learning frameworks like TensorFlow or PyTorch, is essential. You should have a solid understanding of statistical modeling, predictive analytics, and various machine learning techniques (e.g., regression, classification, clustering, natural language processing, computer vision). This role requires excellent communication skills to articulate complex technical concepts to both technical and non-technical audiences, and a proven ability to collaborate effectively in a distributed team environment. A passion for continuous learning and staying abreast of the latest advancements in AI and ML is crucial. We are looking for a strategic thinker with a hands-on approach, capable of translating business needs into data-driven solutions and driving impactful innovation.

Total Number of Openings
1
Chevron is accepting online applications for the position Lead Machine Learning Engineer through October 8th, 2025 at **11:59 p.m.** (CST)  
We are seeking a forward-thinking Lead Machine Learning Engineer to evaluate and integrate emerging and start-up Artificial Intelligence (AI) and Machine Learning (ML) solutions that drive value for Chevron. This role blends deep technical expertise in AI and ML with a passion for experimentation, creativity, and solving complex problems in novel ways.
This position is part of the Mechatronics and Digital Labs Team responsible for providing thought leadership, and execution of technology trials of emerging technologies to validate value and technical capability. The function of this role is to partner with the business to identify disruptive and emerging technologies to achieve greater business value, faster. Our team is highly technical, creative, and innovative. We are cross-functional and passionate about delivering creative solutions that drive significant business value first and foremost.
We are looking for a Lead Machine Learning Engineer with the ability to bring their expertise, innovative attitude and excitement for solving complex problems with new technologies and approaches. There will be no shortage of opportunities to lead, innovate, challenge the status quo, and work directly with Data Scientists, Analytics Professionals and Business experts to build and deliver innovative, value driven AI solutions.
**Responsibilities for this position may include but are not limited to:**
+ Partner with Digital Innovation Teams to evaluate and test emerging AI and Machine Learning technologies.
+ Explore and experiment with applications of Generative AI (GenAI), NLP, and computer vision.
+ Stay current with the latest advancements in AI and integrate them into projects.
+ Work collaboratively with a large variety of different teams, including data scientists, data engineers, and solution architects from various organizations within business units and IT
+ Build and maintain robust data pipelines using platforms like Databricks.
+ Deploy models in production using Docker and cloud platforms (e.g., AWS, Azure).
+ Conduct ML tests and experiments to validate hypotheses and improve performance.
+ Consult, identify and frame opportunities to implement AI solutions that help Chevron businesses gain insight and improve decision making, workflow, and automation.
+ Identify data, appropriate technology and architectural design patterns to solve business challenges using analytical tools, AI design patterns and architectures.
+ Transform data science prototypes into appropriate scale solutions in a production environment.
+ Orchestrate and configure infrastructure that assists Data Scientists and analysts in building low latency, scalable and resilient machine learning and optimization workloads into an enterprise software product.
+ Run machine learning experiments and fine-tune algorithms to ensure optimal performance.
+ Participate as an active member in embedded Agile team to enable cross training and keep skills current.
+ Desire to learn new technologies and design patterns to continually improve delivery of AI Solutions at scale.
**Required Qualifications:**
+ BS in Computer Science, Mathematics, or related fields or equivalent experience.
+ 5+ years' experience in Software Engineering.
+ Significant experience engineering solutions in Python with strong understanding of control flow, functions, data structures and object-oriented programming concepts.
+ Experience implementing machine learning frameworks and libraries (e.g. ML Flow, Kubeflow, Tensorflow. Keras scikit-learn, PyTorch, NumPy, SciPy, etc.).
+ Development experience with a JavaScript framework (Angular, React, node.js etc.).
+ Experience building machine learning pipelines in Microsoft Azure Machine Learning service.
+ Experience developing cloud first solutions using Microsoft Azure Services (Azure Functions, Azure App Services, Azure Event hubs, Azure SQL DB, Azure Synapse etc.).
+ Proficient in applying common design patterns, ability to communicate design ideas effectively.
+ Must have a disciplined, methodical, minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications.
+ Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms.
+ Knowledge of data engineering and transformation tools and patterns such as DataBricks, Spark, Azure Data Factory.
**Preferred Qualifications:**
+ MS in Computer Science, Mathematics, or related fields.
+ Excellent skills in statistics and machine learning applied to timeseries data analysis.
+ Are proficient orchestrating large-scale ML/DL jobs, leveraging big data tooling and modern container orchestration infrastructure (e.g. Kubernetes), to tackle distributed training and massive parallel model executions on cloud infrastructure.
+ Experience designing custom APIs for machine learning models for training and inference processes.
+ Experience designing, implementing, and delivering frameworks for MLOps.
+ Experience implementing and incorporating ML models on unstructured data using cognitive services and/or computer vision as part of AI solutions and workflows.
+ History of working with large scale model optimization and hyperparameter tuning, applied to ML/DL models.
+ Hands-on experience in deploying machine learning pipelines with Azure Machine Learning SDK.
+ Exceptional object-oriented programming and debugging skills in Python.
+ A keen eye for good architecture and the ability to develop new architectures and frameworks.
+ Passionate and detailed approach to software development.
+ Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support.
+ Mature software engineering skills, such as source control versioning, requirement spec, architecture and design review, testing methodologies, CI/CD, etc.
+ Proven ability to take leadership role in projects that span multiple teams, ability to deliver on time working in a fast-paced agile environment, ability to work with product managers to clarify and prune requirements, strong verbal and written communication.
+ Experience working with data scientists in the integration of and delivery of models for advanced analytics use cases.
**Relocation Options:**
Relocation is not offered for this role. Only local candidates will be considered.
**International Considerations:**
Expatriate assignments **will not** be considered.
Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.
U.S. Regulatory notice:
Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin or ancestry, age, mental or physical disability, medical condition, reproductive health decision-making, military or veteran status, political preference, marital status, citizenship, genetic information or other characteristics protected by applicable law.
We are committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance or an accommodation, please email us at .
Chevron participates in E-Verify in certain locations as required by law.
Chevron Corporation is one of the world's leading integrated energy companies. Through its subsidiaries that conduct business worldwide, the company is involved in virtually every facet of the energy industry. Chevron explores for, produces and transports crude oil and natural gas; refines, markets and distributes transportation fuels and lubricants; manufactures and sells petrochemicals and additives; generates power; and develops and deploys technologies that enhance business value in every aspect of the company's operations. Chevron is based in Houston, Texas. More information about Chevron is available at .
Chevron is an Equal Opportunity / Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status, or other status protected by law or regulation.

Our client is a cutting-edge technology company in **Houston, Texas, US**, specializing in advanced AI solutions. We are seeking a talented Machine Learning Engineer with a focus on Natural Language Processing (NLP) to join our dynamic, remote-first team. In this role, you will design, develop, and deploy sophisticated NLP models and algorithms to extract insights from unstructured text data, enhance natural language understanding, and build intelligent conversational agents. You will work with large-scale datasets, leverage state-of-the-art deep learning frameworks, and collaborate with researchers and software engineers to bring innovative AI features to life. This is an exciting opportunity to contribute to impactful projects and shape the future of human-computer interaction.

Responsibilities:

• Develop and implement advanced NLP models for tasks such as text classification, sentiment analysis, named entity recognition, machine translation, and summarization.
• Design and build robust data pipelines for collecting, cleaning, and pre-processing large volumes of text data.
• Train, evaluate, and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or Keras.
• Deploy NLP models into production environments, ensuring scalability, performance, and reliability.
• Collaborate with product managers and software engineers to integrate NLP capabilities into client-facing applications.
• Conduct research on state-of-the-art NLP techniques and algorithms, and apply them to solve business problems.
• Perform feature engineering and model optimization to improve accuracy and efficiency.
• Develop metrics and dashboards for monitoring model performance and identifying areas for improvement.
• Stay current with the latest advancements in NLP, machine learning, and artificial intelligence.
• Document algorithms, models, and processes thoroughly.

Qualifications:

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field.
• 3+ years of professional experience in Machine Learning Engineering, with a strong specialization in NLP.
• Proficiency in Python and relevant ML/NLP libraries (e.g., spaCy, NLTK, Hugging Face Transformers, Scikit-learn).
• Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).
• Solid understanding of NLP concepts, algorithms, and architectures (e.g., RNNs, LSTMs, Transformers).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices is a plus.
• Strong data manipulation and analysis skills.
• Excellent problem-solving and analytical abilities.
• Effective communication and collaboration skills for working in a remote team environment.
• Experience with large-scale data processing frameworks (e.g., Spark) is beneficial.

If you are a passionate NLP expert looking to make a significant impact on AI innovation from **Houston, Texas, US** (or any remote location in the US), we encourage you to apply.

Our client, a leader in AI and Emerging Technologies, is seeking a brilliant and innovative AI Research Scientist specializing in Machine Learning. This role is based in **Houston, Texas, US**, and is ideal for a candidate passionate about pushing the boundaries of artificial intelligence. You will be instrumental in conducting cutting-edge research, developing novel algorithms, and implementing advanced machine learning models to solve complex problems across various domains. This hybrid role offers the opportunity to collaborate closely with a world-class team of researchers and engineers while enjoying flexibility in your work arrangement.
Responsibilities:

• Conduct research in machine learning, deep learning, and related AI fields.
• Design, develop, and implement advanced ML models and algorithms.
• Analyze large datasets to identify patterns, insights, and opportunities for AI applications.
• Collaborate with cross-functional teams to integrate AI solutions into products and services.
• Stay abreast of the latest advancements in AI and machine learning research.
• Publish research findings in leading conferences and journals.
• Develop prototypes and proof-of-concepts for new AI technologies.
• Evaluate and benchmark the performance of ML models.
• Mentor junior researchers and engineers.
• Contribute to the strategic direction of the company's AI initiatives.

Qualifications:

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven track record of research in machine learning, demonstrated through publications, patents, or significant contributions to open-source projects.
• Strong theoretical understanding of various ML algorithms (e.g., deep learning, reinforcement learning, supervised/unsupervised learning).
• Proficiency in programming languages such as Python, and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with large-scale data processing and distributed computing frameworks.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to articulate complex technical concepts.
• Experience with cloud computing platforms (AWS, Azure, GCP) is a plus.
• Ability to work independently and as part of a research team in a hybrid environment.

This is a unique opportunity to work on groundbreaking AI research with a team of highly motivated professionals. Our client offers a competitive compensation package, generous benefits, and a stimulating work environment that fosters innovation. If you are a visionary researcher eager to make a significant impact in the field of AI, we encourage you to apply.

**Job Description**
**Job Summary**
Responsible for overseeing data science projects, managing and mentoring a team, and aligning data initiatives with business goals. Lead the development and implementation of data models, collaborate with cross-functional teams, and stay updated on industry trends. Ensure ethical data use and communicate complex technical concepts to non-technical stakeholders. Lead initiatives on model governance and model ops to align with regulatory and security requirements. This role requires technical expertise, strategic thinking, and leadership to drive data-driven decision-making within the organization and be the pioneer on generative AI healthcare solutions, aimed at revolutionizing healthcare operations as well as enhancing member experience.
**Job Duties**
- **Research and Development:** Stay current with the latest advancements in AI and machine learning and apply these insights to improve existing models and develop new methodologies.
- **AI Model Deployment, Monitoring & Model Governance:** Deploy AI models into production environments, monitor their performance, and adjust as necessary to maintain accuracy and effectiveness and meet all governance and regulatory requirements.
- **Innovation Projects:** Lead pilot projects to test and implement new AI technologies within the organization
- **Data Analysis and Interpretation:** Extract meaningful insights from complex datasets, identify patterns, and interpret data to inform strategic decision-making.
- **Machine Learning Model Development** : Design, develop, and train machine learning models using a variety of algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- **Agentic Workflows Implementation:** Develop and implement agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities.
- **RAG Pattern Utilization:** Employ retrieval-augmented generation patterns to improve the performance of language models, ensuring they can access and utilize external knowledge effectively to enhance their outputs.
- **Model Fine-Tuning** : Fine-tune pre-trained models to adapt them to specific tasks or datasets, ensuring optimal performance and relevance in various applications.
- **Data Cleaning and Preprocessing:** Prepare data for analysis by performing data cleaning, handling missing values, and removing outliers to ensure high-quality inputs for modeling.
- **Collaboration:** Work closely with cross-functional teams, including software engineers, product managers, and business analysts, to integrate AI solutions into existing systems and processes.
- **Documentation and Reporting:** Create comprehensive documentation of models, methodologies, and results; communicate findings clearly to non-technical stakeholders.
- Mentors, coaches, and provides guidance to newer data scientists.
- Partner closely with business and other technology teams to build ML models which helps in improving Star ratings, reduce care gap and other business objectives.
- Present complex analytical information to all level of audiences in a clear and concise manner Collaborate with analytics team, assigning and managing delivery of analytical projects as appropriate
- Perform other duties as business requirements change, looking out for data solutions and technology enabled solution opportunities and make referrals to the appropriate team members in building out payment integrity solutions.
- Use a broad range of tools and techniques to extract insights from current industry or sector trends
**Job Qualifications**
**REQUIRED EDUCATION:**
Master's Degree in Computer Science, Data Science, Statistics, or a related field
**REQUIRED EXPERIENCE/KNOWLEDGE, SKILLS & ABILITIES:**
- 10+ years' work experience as a data scientist preferably in healthcare environment but candidates with suitable experience in other industries will be considered
- Knowledge of big data technologies (e.g., Hadoop, Spark)
- Familiar with relational database concepts, and SDLC concepts
- Demonstrate critical thinking and the ability to bring order to unstructured problems
- **Technical Proficiency:** Strong programming skills in languages such as Python and R, and experience with machine learning frameworks like TensorFlow, Keras, or PyTorch.
- **Statistical Analysis:** Excellent understanding of statistical methods and machine learning algorithms, including k-NN, Naive Bayes, SVM, and neural networks.
- **Experience with Agentic Workflows:** Familiarity with designing and implementing agentic workflows that leverage AI agents for autonomous operations.
- **RAG Techniques:** Knowledge of retrieval-augmented generation techniques and their application in enhancing AI model outputs.
- **Model Fine-Tuning Expertise:** Proven experience in fine-tuning models for specific tasks, ensuring they meet the required performance metrics.
- **Data Visualization:** Proficiency in data visualization tools (e.g., Tableau, Power BI) to present complex data insights effectively.
- **Database Management:** Experience with SQL and NoSQL databases, data warehousing, and ETL processes.
- **Problem-Solving Skills:** Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex challenges.
**PREFERRED EDUCATION:**
PHD or additional experience
**PREFERRED EXPERIENCE:**
- Experience with cloud platforms (e.g., Databricks, Snowflake, Azure AI Studio etc.) for working with AI workflows and deploying models.
- Familiarity with natural language processing (NLP) and computer vision techniques.
#PJCorp2
#LI-AC1
To all current Molina employees: If you are interested in applying for this position, please apply through the intranet job listing.
Molina Healthcare offers a competitive benefits and compensation package. Molina Healthcare is an Equal Opportunity Employer (EOE) M/F/D/V.
Pay Range: $117,731 - $275,491 / ANNUAL
*Actual compensation may vary from posting based on geographic location, work experience, education and/or skill level.

Our client, a cutting-edge AI research and development firm, is looking for a talented Senior Machine Learning Engineer with a strong specialization in Natural Language Processing (NLP) to join their dynamic, fully remote team. This role offers the opportunity to work on groundbreaking AI projects that push the boundaries of what's possible. You will be instrumental in designing, developing, and deploying advanced NLP models for a variety of applications, including text analysis, sentiment detection, conversational AI, and information extraction. Responsibilities include researching and implementing state-of-the-art NLP algorithms, building and optimizing deep learning models, and creating robust data pipelines for training and evaluation. You will collaborate with cross-functional teams of researchers, software engineers, and product managers to translate complex business problems into effective AI solutions. The ideal candidate possesses a deep understanding of NLP concepts such as transformers, recurrent neural networks, and attention mechanisms, along with extensive experience in programming languages like Python and relevant libraries (e.g., TensorFlow, PyTorch, Hugging Face). Proven experience with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks is highly desirable. You will also be expected to contribute to the broader ML community through publications or open-source contributions. This is a remote-first position, emphasizing asynchronous communication, clear documentation, and self-discipline. The ability to work independently and proactively manage your workload in a virtual environment is paramount. A Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, combined with at least 5 years of professional ML engineering experience, with a significant focus on NLP, is required. If you are passionate about advancing the field of AI and want to make a significant impact from anywhere in the world, we encourage you to apply.