27 Machine Learning jobs in Pasadena

Tekmetric is a cloud-based auto-repair shop management system with an easy-to-use workflow and a modern approach to customer care. Tekmetric champions transparency, integrity, innovation—and above all—a service-mentality that puts customers first. Founded in Houston, Texas in 2015, Tekmetric has been providing reliable, fast customer service to shops from day one. Our team is growing quickly, but our service philosophy of listening to customers still remains a core value. We’re looking for hungry candidates to help us strengthen our industry-leading team. We’re building our software to be more intuitive. We’re building more integrations that make our customers’ lives easier. We’re building better internal processes to make our globally distributed organization run more smoothly. We’re building stronger relationships with the best and brightest partners in our industry. Our customers love our products. We love serving them. And we love the journey we’re on together. What You’ll Do We are looking for a Machine Learning Engineer specializing in NLP, document classification, and large-scale data processing. You will work on applying LLMs, NLP, and ML techniques to categorize and process extracted data. Your work will power an intelligent search system and help organize massive amounts of structured and unstructured information. Develop and train NLP & ML models for document classification, text extraction, and entity recognition. Experiment with LLMs (GPT, Llama, Claude, etc.), embeddings, transformers, and vector databases. Build pipelines that combine rule-based methods with ML models for classification. Apply OCR techniques to extract structured data from PDFs and scanned documents. Fine-tune and optimize models for scalability, latency, and cost-efficiency. Deploy ML models in production using Kubernetes, AWS (SageMaker, Lambda, EMR), and Airflow. Collaborate with data engineers to integrate ML models into search APIs and data pipelines. Utilize Spark (EMR) or distributed computing for large-scale ML processing. What You’ll Bring 3+ years of experience in Machine Learning & NLP. Strong Python skills and experience with ML/NLP frameworks like Hugging Face, spaCy, NLTK, TensorFlow, PyTorch etc. Familiarity with transformer-based architectures (BERT, GPT, T5, etc.). Experience with text classification, embeddings. Knowledge of OCR (Tesseract, Amazon Textract, or OpenCV-based techniques). Hands-on experience with AWS services, Kubernetes, and workflow orchestration (Airflow). Strong understanding of information retrieval, search ranking, and ElasticSearch/OpenSearch. Nice to Have Experience fine-tuning LLMs for domain-specific applications. Experience with RAG and vector databases (FAISS, Pinecone, Weaviate, Vespa, etc.). Working knowledge of knowledge graphs, embeddings, or multimodal ML. Experience optimizing ML models for real-time processing in production environments. Who You Are Successful candidates will also demonstrate many of the characteristics that our core values represent: Build things that matter: You have a love of building something new or improving on current processes and care about making a positive difference. You love learning new things and are comfortable working in a startup-like, dynamic environment -- moving quickly, even in the face of ambiguity. You are a self-directed leader who can jump in, structure their own work, and figure out how best to execute a plan yourself and with others. At Tekmetric our leaders are all players and coaches. Yes before no: You keep an open mind and are excited about new ideas and helping others actualize their ideas. You are intellectually curious and analytical in a strategic context. We matter to each other: You care about people and see the success of one as success for us all. You are a highly ethical individual with unquestioned integrity and the experience, confidence, and stature to protect confidential information in a growing company. What We Offer: Flexible and remote work opportunities. Generous PTO. Exceptional leave programs for all of life’s moments: maternity, paternity and parental bonding, as well as medical leave to care for yourself or loved ones. Excellent Medical, Dental, Vision and Prescription Drug Coverage. 401(k) Retirement Savings Plan with a 6% Match. Employer covered STD, LTD, Life and AD&D Insurance Programs. Up to $60 monthly for wellness expenses and activities. Education Assistance- includes undergraduate/graduate courses and continuing education. Most importantly, we have a stellar team of coworkers, a really cool office, and lots of fun activities! Tekmetric is an equal opportunity employer. We hire hard working individuals, regardless of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, or veteran status. We know that when our employees feel appreciated and included, they can be more creative, innovative and successful. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. #J-18808-Ljbffr

• Design, develop, and implement machine learning models from conceptualization to production deployment, focusing on areas like predictive maintenance, resource optimization, and data anomaly detection.
• Work with large, complex datasets, performing data cleaning, feature engineering, and data preprocessing to prepare for model training.
• Evaluate and select appropriate ML algorithms and frameworks for specific problems, including deep learning, reinforcement learning, and traditional ML techniques.
• Develop and optimize model architectures, training pipelines, and evaluation metrics.
• Deploy, monitor, and maintain ML models in production environments, ensuring performance, reliability, and scalability.
• Collaborate closely with data scientists, software engineers, domain experts, and product managers to understand requirements and integrate ML solutions.
• Conduct research to stay current with the latest advancements in AI and machine learning, and apply relevant techniques.
• Write clean, efficient, and well-documented code in Python, adhering to software engineering best practices.
• Communicate complex technical concepts and model results to non-technical stakeholders.
• Contribute to the overall AI strategy and development of the company's core technological capabilities.

• Master's or Ph.D. in Computer Science, Machine Learning, Electrical Engineering, Statistics, or a related quantitative field.
• Minimum of 3-5 years of experience as a Machine Learning Engineer or Data Scientist with a focus on model deployment.
• Strong programming skills in Python; experience with other languages like Java or C++ is a plus.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and libraries like Pandas, NumPy.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment and management.
• Solid understanding of machine learning algorithms, statistical modeling, and data structures.
• Experience with large-scale data processing technologies (e.g., Spark, Hadoop) is highly desirable.
• Excellent problem-solving skills, analytical thinking, and attention to detail.
• Strong communication and collaboration skills.
• Domain knowledge in the energy sector is a significant advantage.

Join us to shape the way energy trades in the future The energy we use to power our daily lives is delivered through pipelines, on ships, via truck and rail, and in wires and batteries. As a leading energy trader, Vitol is at the heart of energy markets worldwide, moving more than 5% of the world’s energy, every single day. For 50 years we’ve challenged the status quo, looking for opportunities to create efficiencies and improve performance, and the recent explosion of data in the industry is just the next step in that journey. Today’s energy markets face new challenges: changes in the way people consume energy, rising economic powers, new technologies, and geo-political shifts are changing the energy landscape, not to mention the COVID-19 pandemic and the beginning of the global energy transition. The Data Science team works closely with the commercial decision makers, using cutting edge machine learning to shape our understanding of the world’s energy markets, identify new opportunities and turn data into impactful decision making. This is an opportunity to join a friendly, entrepreneurial and non-hierarchical environment, in a fun and agile team, and help revolutionize the way data is used within the organization. About Vitol Vitol is an energy and commodities company with revenues of $400 billion in 2023; its primary business is the trading and distribution of energy products globally – it trades over seven million barrels per day of crude oil and products and, at any time, has 250 ships transporting its cargoes. Vitol’s clients include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves clients from some 40 offices worldwide and is invested in energy assets globally including 16mm3 of storage, 480kbpd of refining capacity, and 7,000 service stations. To date, we have committed over $2.5 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world. Who are we? Our people are our business: the company’s value derives ultimately from them. It is on their expertise, innovation, drive and relationships that we depend for the development and growth of our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unfettered by hierarchy. Our business is global and our people are as diverse as the world in which we work. We have over 60 nationalities among our team – giving us a diversity of thinking which we believe translates into a greater understanding of our customers and better and more informed decisions. Job Description As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and technologies. The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models. The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the ‘art of the possible’. Core Responsibilities include: Being an energetic and enthusiastic member of a team uniquely positioned to bring the power of data to bear on the inner workings of the energy industry Ability to relate effortlessly with the commercial side of the business, being a thought leader and looking for new ways how AI/DS can create value for Vitol Leading design, development, and deployment of machine learning systems, bringing their technical knowledge and experience into the team, and using this to create real solutions to real problems. Prioritization of projects based on changing business conditions and a keen eye for where maximum value can be delivered Collaborating with cross-functional technology teams to gather requirements and ensure the solutions align with business objectives Helping integrate the team’s solutions (including GenAI) into existing systems and platforms to provide seamless user experiences and scale adoption Actively participating in code reviews, experiment design and tooling decisions to help drive the team’s velocity and quality Helping build data and machine learning expertise within the business through knowledge sharing Qualifications Master's degree in Computer Science, Data Science, Machine Learning, or a related field. Ph.D. is a plus Fluency in Python with the ability to write clean, modular, well-documented code as well as a solid understanding of coding best practices 5-7+ years in industry developing and deploying machine learning models, preferably in NLP, LLM and ideally generative AI domains Experience in successfully applying LLMs to solve business problems, solid understanding of Gen AI design paradigms and best practices Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Transformers Familiarity with cloud platforms (AWS) and containerization technologies (Docker) Excellent problem-solving skills, ability to work independently and in a team Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders Understanding of machine learning fundamentals, including deep learning, generative models, NLP techniques, such as sentiment analysis, and entity recognition and disambiguation Additional Information Desired Experience Practical, real world (production) experience with Gen AI based models and their applications Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts Experience integrating machine learning systems into interactive dashboards (e.g. Dash, Streamlit) and present use cases of machine learning to non-technical colleagues Time series modelling (both machine-learning and econometric approaches) Application of a wide range of ML methodologies to real life applications Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines Awareness of continuous integration and delivery concepts/technologies Personal Characteristics A self-motivated individual who thrives on seeing the results of their work make an impact in the business Strong communication skills, both verbally and in writing Proven ability to be flexible, work hard, and a sense for the art of the possible Methodical, organized and with an attention to detail - in general, in experimental design, and in code! Willingness to share their knowledge and learn from others An interest in learning about the commodities space Resourceful, able to think creatively and adapt in a dynamic environment Team player, with an open non-political style and a high level of integrity Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world’s energy flows What we offer Competitive salary and benefits package Large diversity of projects with real-world impacts on a truly global scale Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva) A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry Strong management commitment to incorporating machine learning into the future of Vitol’s operations All your information will be kept confidential according to EEO guidelines. #J-18808-Ljbffr

• Design, develop, and implement end-to-end machine learning pipelines, from data ingestion and feature engineering to model training, evaluation, and deployment.
• Build and optimize machine learning models (e.g., deep learning, NLP, computer vision, traditional ML) for various applications, ensuring scalability and performance.
• Collaborate closely with data scientists, software engineers, and product managers to translate business requirements into technical specifications and ML solutions.
• Conduct thorough research and experimentation with new ML algorithms, frameworks, and technologies to enhance existing models and develop innovative solutions.
• Deploy machine learning models into production environments, monitoring their performance and ensuring continuous improvement.
• Optimize model inference and training for efficiency and cost-effectiveness.
• Lead code reviews, provide constructive feedback, and ensure adherence to best practices in machine learning engineering.
• Develop and maintain robust MLOps practices, including version control, CI/CD for ML, and model monitoring.
• Troubleshoot and debug complex issues related to ML models and data pipelines.
• Mentor junior machine learning engineers and contribute to the growth of the team's technical capabilities.
• Document model specifications, design choices, and deployment procedures.

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
• Minimum of 5-7 years of professional experience in machine learning engineering or data science with a strong engineering focus.
• Expert proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps tools (e.g., MLflow, Kubeflow, Sagemaker).
• Solid understanding of machine learning algorithms, statistical modeling, and data structures.
• Experience with big data technologies (e.g., Spark, Hadoop) and data warehousing is a plus.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration abilities, capable of working effectively in cross-functional teams.
• Proven track record of deploying ML models into production.
• Experience with containerization (Docker, Kubernetes) is highly desirable.

• Design, develop, and implement advanced machine learning models and algorithms for various applications, from concept to production.
• Build and optimize scalable data pipelines for training and inference of ML models.
• Collaborate closely with data scientists to translate research prototypes into production-ready solutions.
• Perform data preprocessing, feature engineering, and model evaluation to ensure high performance and reliability.
• Deploy, monitor, and maintain ML models in production environments, ensuring performance and stability.
• Conduct rigorous experimentation and A/B testing to evaluate model effectiveness and identify areas for improvement.
• Stay current with the latest advancements in machine learning, deep learning, and AI research, and apply relevant techniques.
• Write clean, efficient, and well-documented code in Python or other relevant languages.
• Participate in code reviews, contribute to architectural discussions, and promote best practices in MLOps.
• Communicate complex technical concepts and model performance to both technical and non-technical stakeholders.

• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
• Minimum of 5 years of professional experience as a Machine Learning Engineer or a related role, with a strong portfolio of deployed ML projects.
• Expertise in common ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and deep learning architectures.
• Strong programming skills in Python; experience with other languages (e.g., Java, C++) is a plus.
• Proficiency with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
• Solid understanding of MLOps principles, including model versioning, monitoring, and deployment strategies.
• Excellent analytical, mathematical, and problem-solving skills.
• Strong written and verbal communication skills, capable of explaining complex technical concepts clearly.

• Experience with big data technologies (e.g., Spark, Hadoop).
• Knowledge of distributed computing and GPU optimization.
• Contributions to open-source ML projects or academic publications.

Are you looking for an exciting opportunity to solve exciting business problems in the domain of Network infrastructure? You will be expected to apply your strong curiosity for data and your proven track record of successfully applying rigorous scientific methods with a proficiency in ML Engineering and DevOps capabilities. Enhance operational efficiency by solving problems and aligning with business goals. As an Vice President Machine Learning Engineer within our dynamic team, you will spearhead the development and implementation of AI / ML solutions to address intricate business challenges. This role offers an exciting platform to utilize your keen interest in data, your expertise in ML Engineering and DevOps, and your multifaceted skills to make a significant impact on global business. You will work in collaboration with cross-functional teams, design and develop AI / ML models, and oversee their deployment into production, all while handling vast amounts of data. Job Responsibilities : - Develop and implement AI / ML models and algorithms to solve business problems. - Collaborate with cross-functional teams to understand requirements and translate them into technical solutions. - Design and develop data pipelines to preprocess and transform data for AI / ML models. - Train and evaluate AI / ML models using large datasets. - Optimize and fine-tune AI / ML models for performance and accuracy. - Deploy AI / ML models into production environments. - Monitor and maintain deployed models, ensuring their performance and reliability. - Stay up-to-date with the latest advancements in AI / ML technologies and techniques. - Be responsible for designing graph data models specifically for algorithm optimization. - Be responsible for designing and adding the data from the physical and logical infrastructure components and their relationships. - Developing and implementing data ETL pipelines within AWS Required qualifications, capabilities, and skills : - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - Atleast 5 years of demonstrated experience in applied AI / ML engineering. - Strong programming skills in Python, with experience in developing and maintaining production-level code. - Experience with designing and implementing graph databases, such as Amazon Neptune, TigerGraph. - Proficiency in working with large datasets and data preprocessing. - Solid understanding of AI / ML algorithms and techniques, including deep learning, reinforcement learning, and natural language processing. - Familiarity with AI / ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras. - Experience in creating infrastructure graph data models - Experience with cloud platforms, such as AWS or Azure, for deploying and scaling AI / ML models. - Experience with ETL tools such as Airflow, and Jenkins. Strong problem-solving and analytical skills. - Excellent communication and collaboration skills. Knowledge of infrastructure operations Preferred Qualifications, capabilities and skills - Experience with distributed computing frameworks, such as Apache Spark. - Knowledge of graph-based AI / ML algorithms and techniques. - Familiarity with DevOps practices for AI / ML model deployment and monitoring. JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and / or discretionary incentive compensation, paid in the form of cash and / or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability / Veterans Base Pay / Salary Jersey City,NJ $164,350.00 - $260,000.00 / year Create a job alert for this search Machine Learning Engineer • Houston, TX, US #J-18808-Ljbffr

• Lead the full lifecycle development of AI/ML models, from data ingestion and feature engineering to model training, evaluation, and deployment.
• Design and implement scalable machine learning pipelines using cloud platforms (e.g., AWS, Azure, GCP).
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define project requirements and deliver integrated solutions.
• Research and evaluate new AI/ML technologies and methodologies to continuously improve existing systems and explore novel applications.
• Mentor junior engineers and contribute to the growth of the team's technical capabilities and best practices.
• Ensure the performance, reliability, and security of AI/ML applications in production environments.
• Develop and maintain comprehensive documentation for models, pipelines, and systems.
• Stay abreast of industry trends and advancements in AI, machine learning, and emerging technologies.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• 5+ years of professional experience in developing and deploying AI/ML solutions in a production environment.
• Strong proficiency in Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Extensive experience with data processing, feature engineering, and model optimization techniques.
• Familiarity with MLOps principles and tools for model deployment, monitoring, and versioning.
• Experience with cloud computing platforms (AWS, Azure, or GCP).
• Excellent problem-solving skills and the ability to work independently and as part of a collaborative team.
• Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.

• Experience with big data technologies (Spark, Hadoop).
• Knowledge of containerization (Docker, Kubernetes).
• Prior experience in a leadership or mentoring role.
• Publications in top-tier AI/ML conferences or journals.

As an Vice President Machine Learning Engineer within our dynamic team, you will spearhead the development and implementation of AI/ML solutions to address intricate business challenges. This role offers an exciting platform to utilize your keen interest in data, your expertise in ML Engineering and DevOps, and your multifaceted skills to make a significant impact on global business. You will work in collaboration with cross-functional teams, design and develop AI/ML models, and oversee their deployment into production, all while handling vast amounts of data.

Job Responsibilities:

- Develop and implement AI/ML models and algorithms to solve business problems.

- Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.

- Design and develop data pipelines to preprocess and transform data for AI/ML models.

- Train and evaluate AI/ML models using large datasets.

- Optimize and fine-tune AI/ML models for performance and accuracy.

- Deploy AI/ML models into production environments.

- Monitor and maintain deployed models, ensuring their performance and reliability.

- Stay up-to-date with the latest advancements in AI/ML technologies and techniques.

- Be responsible for designing graph data models specifically for algorithm optimization.

- Be responsible for designing and adding the data from the physical and logical infrastructure components and their relationships.

- Developing and implementing data ETL pipelines within AWS

Required qualifications, capabilities, and skills:

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Atleast 5 years of demonstrated experience in applied AI/ML engineering.

- Strong programming skills in Python, with experience in developing and maintaining production-level code.

- Experience with designing and implementing graph databases, such as Amazon Neptune, TigerGraph.

- Proficiency in working with large datasets and data preprocessing.

- Solid understanding of AI/ML algorithms and techniques, including deep learning, reinforcement learning, and natural language processing.

- Familiarity with AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras.

- Experience in creating infrastructure graph data models

- Experience with cloud platforms, such as AWS or Azure, for deploying and scaling AI/ML models.

- Experience with ETL tools such as Airflow, and Jenkins. Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills. Knowledge of infrastructure operations

Preferred Qualifications, capabilities and skills

- Experience with distributed computing frameworks, such as Apache Spark.

- Knowledge of graph-based AI/ML algorithms and techniques.

- Familiarity with DevOps practices for AI/ML model deployment and monitoring.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

Base Pay/Salary
Jersey City,NJ $164,350.00 - $260,000.00 / year