162 Senior Machine Learning Engineer jobs in Los Angeles

• Design, build, and deploy machine learning models and pipelines.
• Develop and maintain scalable ML systems on cloud platforms.
• Perform data preprocessing, feature engineering, and model training.
• Optimize model performance, accuracy, and efficiency.
• Implement MLOps practices for model deployment, monitoring, and lifecycle management.
• Collaborate with data scientists and software engineers to integrate ML solutions.
• Evaluate and experiment with new ML algorithms and technologies.
• Troubleshoot and resolve issues related to ML models and infrastructure.
• Document ML models, processes, and best practices.
• Contribute to the overall AI/ML strategy and roadmap.

• Master's or Ph.D. in Computer Science, Statistics, or a related quantitative field.
• 5+ years of experience in machine learning engineering or applied data science.
• Proficiency in Python and core ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with cloud ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform).
• Strong understanding of MLOps principles and tools.
• Experience with big data technologies (e.g., Spark) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities in a remote environment.

• Design, develop, and implement scalable machine learning models and algorithms
• Build and maintain robust ML pipelines for data processing, model training, and inference
• Collaborate with data scientists, software engineers, and product managers to define and deliver ML solutions
• Optimize ML models for performance, efficiency, and accuracy
• Deploy ML models into production environments and monitor their performance
• Research and evaluate new ML technologies and techniques
• Mentor and guide junior machine learning engineers and data scientists
• Lead technical discussions and contribute to architectural decisions for ML systems
• Troubleshoot and resolve complex issues in ML systems
• Contribute to the company's ML strategy and roadmap

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field
• Minimum of 8 years of experience in machine learning engineering or related roles
• Extensive experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Strong programming skills in Python and proficiency in languages like C++ or Java
• Proven experience in deploying and managing ML models in production at scale
• Deep understanding of various ML algorithms, including deep learning, supervised, and unsupervised learning
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices
• Excellent problem-solving, analytical, and critical-thinking skills
• Strong communication and collaboration abilities
• Experience leading technical projects and mentoring teams.

• Design, develop, and implement machine learning models and algorithms.
• Build and maintain scalable ML pipelines for training, evaluation, and deployment.
• Collaborate with cross-functional teams to identify and address business challenges with ML solutions.
• Perform data preprocessing, feature engineering, and model selection.
• Deploy ML models into production environments and monitor their performance.
• Conduct research on new ML techniques and technologies.
• Optimize model performance and efficiency.
• Mentor junior machine learning engineers and contribute to knowledge sharing.
• Ensure the ethical and responsible use of AI and ML technologies.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience in machine learning engineering or data science.
• Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, Keras, PyTorch, TensorFlow).
• Proficiency in MLOps practices and tools (e.g., Docker, Kubernetes, CI/CD).
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Solid understanding of data structures, algorithms, and software engineering principles.
• Excellent analytical, problem-solving, and communication skills.
• Experience working in a remote, collaborative team environment.

• Lead the design, development, and deployment of advanced machine learning models and algorithms.
• Architect and build scalable ML systems and infrastructure.
• Conduct research into new ML techniques and technologies to solve challenging business problems.
• Collaborate with product managers and engineers to define ML requirements and product roadmaps.
• Develop and implement strategies for data collection, preprocessing, and feature engineering.
• Train, evaluate, and deploy ML models, ensuring optimal performance and robustness.
• Troubleshoot and debug complex ML systems and pipelines.
• Mentor and guide junior machine learning engineers and data scientists.
• Drive best practices in ML development, including version control, testing, and MLOps.
• Stay current with the latest advancements in AI, machine learning, and related fields.
• Communicate technical findings and recommendations to both technical and non-technical stakeholders.
• Contribute to the overall technical vision and strategy for AI/ML at the company.

• Ph.D. or M.S. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 10+ years of professional experience in machine learning or a related field, with a significant portion in a senior or lead capacity.
• Proven track record of successfully developing and deploying production-level ML models.
• Deep expertise in ML algorithms, statistical modeling, and data mining techniques.
• Proficiency in programming languages such as Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and distributed computing frameworks.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Strong understanding of MLOps principles and tools for managing the ML lifecycle.
• Excellent problem-solving, analytical, and critical thinking skills.
• Exceptional communication and leadership skills, suitable for a remote-first environment.

• Design, develop, and deploy advanced NLP models and algorithms.
• Conduct research and experimentation to identify novel approaches for NLP tasks.
• Process and analyze large, unstructured text datasets.
• Implement and optimize ML pipelines for scalability and efficiency.
• Collaborate with cross-functional teams to integrate AI solutions into products.
• Stay current with the latest advancements in AI, ML, and NLP research.
• Mentor junior engineers and contribute to team knowledge sharing.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
• 5+ years of experience in machine learning, with a strong focus on NLP.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Expertise in NLP techniques (e.g., sentiment analysis, named entity recognition, topic modeling, text generation).
• Experience with LLMs and transformer architectures.
• Strong understanding of data structures, algorithms, and software engineering best practices.
• Excellent communication and collaboration skills.

About Gusto

About Gusto

Gusto is a modern, online people platform that helps small businesses take care of their teams. On top of full-service payroll, Gusto offers health insurance, 401(k)s, expert HR, and team management tools. Today, Gusto offices in Denver, San Francisco, and New York serve more than 400,000 businesses nationwide.

Our mission is to create a world where work empowers a better life, and it starts right here at Gusto. That’s why we’re committed to building a collaborative and inclusive workplace, both physically and virtually. Learn more about our Total Rewards philosophy.

About the role

Gusto’s Data Science team leverages Gusto’s rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers.

For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem.

You’ll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world-class, high secure platform that safeguards our users’ activities and money, and ensures unparalleled reliability.

• Build and deploy machine learning models to identify, assess and mitigate risks
• Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time
• Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems
• Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities
• Identify new opportunities to leverage data to improve Gusto’s products and help risk management team to understand business requirements and develop tailored solutions
• Present and communicate results to stakeholders across the company

• 8+ years experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning.
• Proven experience in the credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks
• Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional).
• Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development all the way through to deployment
• Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion
• PhD or Masters plus equivalent experience in a quantitative field is a plus
• Experience in the Fintech industry is a plus

Our cash compensation amount for this role is targeted at $170,000 - $05,000 in Denver, 185,000- 225,000 in Los Angeles, 205,000 - 250,000 for San Francisco, New York, and Seattle, and 185,000 - 225,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gustos subsidiary, whose physical office is in Scottsdale.

Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.

When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required.

Our customers come from all walks of life and so do we. We hire great people from a wide variety of backgrounds, not just because its the right thing to do, but because it makes our company stronger. If you share our values and our enthusiasm for small businesses, you will find a home at Gusto.

Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.

Interested in building your career at Gusto, Inc? Get future opportunities sent straight to your email.

We have removed the long-form application content to keep the focus on role details. To apply, please visit the company careers page.

Our customers come from all walks of life and so do we. We hire people from a wide variety of backgrounds, not just because it’s the right thing to do, but because it helps us to build better products, better serve our customers, and makes our company stronger.

In addition to the information required to consider your application, below is a set of demographic questions that help us identify areas for improvement in our process and further support the development and execution of our diversity efforts and programs as well as to create a more inclusive environment for all employees.

Your responses to these questions will be recorded and maintained in a confidential file. Your responses, or your wish not to answer, will not be associated with your specific application, will not be shared with hiring managers, and will not in any way be used in making any employment decisions.

Please use this as a reference while completing the disability self-identification:

• Blindness
• Deafness
• Cancer
• Diabetes
• Epilepsy
• Autism
• Cerebral palsy
• HIV/AIDS
• Bipolar disorder
• Multiple sclerosis (MS)
• Missing limbs or partially missing limbs
• Post-traumatic stress disorder (PTSD)

How would you describe your gender identity (please select one)?

I identify as transgender (please select one):

I identify my sexual orientation as (please select one):

I identify my race/ethnicity as (mark all that apply):

Veteran Status (please select one):

I have a disability (please select one):

I identify as a first-generation professional (please select one):

Overview

About Gusto

Gusto is a modern, online people platform that helps small businesses take care of their teams. On top of full-service payroll, Gusto offers health insurance, 401(k)s, expert HR, and team management tools. Today, Gusto offices in Denver, San Francisco, and New York serve more than 400,000 businesses nationwide.

Our mission is to create a world where work empowers a better life. We’re committed to building a collaborative and inclusive workplace, both physically and virtually.

About the Role

As a Staff Machine Learning Engineer, you will work closely with applied science practitioners and engineers to rapidly build, deploy, and iterate high-quality ML infrastructure solutions at scale, ensuring both reliability and effectiveness. Your deep expertise in the machine learning model development cycle, along with a strong understanding of data pipelines and data infrastructure, will be crucial in developing a dependable and scalable ML infrastructure for all of Gusto to rely on. The ideal candidate is passionate about developing software, documenting optimal processes, working with data, and understanding the needs of end users. A strong grasp of ML and data infrastructure is essential, as you will work with stakeholders to build efficient solutions to help our partners scale x times better.

• Drive core components of our ML Platform technical roadmap to design and build MLOps solutions with automated pipelines and standardized processes to build, deploy, run, monitor, debug, and retrain ML Models.
• Develop, maintain, and enhance frameworks for machine learning model development and deployment.
• Collaborate with the ML model builders and application owners to determine business requirements and SLAs for API-enabled services.
• Develop, maintain, and enhance infrastructure supporting machine learning services.
• Support the development of new patterns for the deployment of machine learning models with CI/CD pipelines and automated testing.

• At least 10 years of software engineering experience (Python, Ruby or Java).
• Demonstrated experience architecting and developing infrastructure and platform services for machine learning lifecycle, such as feature stores, model development, deployment, and observability tools and solutions.
• Experience with at least one of the major cloud platforms (AWS preferred but not required).
• Experience with MLOps tooling such as Kubeflow, AWS Sagemaker, Mlflow, or similar.

Our cash compensation amount for this role is targeted at $157,000-$94,000/year in Denver, 188,000- 222,000/year in Los Angeles, and 190,000- 235,000/year for San Francisco, Seattle and New York. Final offer amounts are determined by multiple factors, including candidate experience and expertise, and may vary from the amounts listed above.

Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gustos subsidiary, whose physical office is in Scottsdale. Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas.

When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required.

Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you.

Interested in building your career at Gusto, Inc? Apply for this job. To apply, please submit your resume and required information.

Our customers come from all walks of life and so do we. We hire people from a wide variety of backgrounds to build better products and serve our customers. The following demographic questions help us identify areas for improvement in our process and further support our diversity efforts. Your responses will be confidential and will not be used in making any employment decisions.

• Disability information: Example list of disabilities

Details related to gender identity, sexual orientation, race/ethnicity, veteran status, and related topics are collected solely for diversity, equity, and inclusion purposes and are not used in making hiring decisions.

• Design, develop, and implement state-of-the-art AI safety and security techniques.
• Build and deploy robust machine learning models with a focus on adversarial robustness, fairness, and explainability.
• Conduct thorough security and safety assessments of AI systems and infrastructure.
• Develop and maintain automated testing frameworks for AI safety evaluations.
• Collaborate with research scientists and engineers to integrate safety features into AI models.
• Research and stay abreast of the latest advancements in AI safety, security, and privacy.
• Document and present findings, methodologies, and recommendations to technical and non-technical audiences.
• Mentor junior engineers and contribute to the team's technical growth.
• Identify and mitigate potential risks associated with AI deployment.
• Contribute to the development of internal tools and libraries for AI safety.

• Ph.D. or Master's degree in Computer Science, Machine Learning, or a related field, with a strong emphasis on AI safety or security.
• Minimum of 10 years of experience in machine learning engineering, with at least 5 years dedicated to AI safety, security, or related areas.
• Expertise in various machine learning techniques, deep learning frameworks (e.g., TensorFlow, PyTorch), and MLOps.
• Proven experience in developing and implementing methods for adversarial robustness, bias detection/mitigation, and model explainability.
• Strong programming skills in Python and C++.
• Excellent understanding of cryptography, secure coding practices, and system security principles.
• Ability to conduct complex research and translate findings into practical engineering solutions.
• Exceptional problem-solving and analytical skills.
• Strong communication and collaboration skills, with experience working in remote teams.
• A proactive mindset and a commitment to building safe and trustworthy AI.