About us

TeleTracking began with a simple but powerful belief that no one should wait for the care they need. More than a slogan, it’s a promise to continually improve healthcare.

TeleTracking builds groundbreaking technology incorporating deep clinical expertise. Our solutions are used in the nation’s largest healthcare systems and around the world to positively impact patients, families and communities.

What’s your contribution to the TeleTracking story?

When you chose to bring your passion and skills to helping achieve our purpose, you’ll be part of a team that understands that there’s a human life behind every data point.   Your skills, curiosity, and compassion—will help fuel our innovation and achieve the TeleTracking promise of revolutionizing modern healthcare. 

About the role

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team at TeleTracking Technologies, focusing on improving patient care. The ideal candidate will have a strong background in developing, deploying, and optimizing machine learning models, as well as expertise in data ingestion and modeling techniques. This role requires a deep understanding of hospital operations, healthcare data, clinical workflows, and regulatory requirements (such as HIPAA or GDPR). The successful candidate will be passionate about leveraging advanced technologies to enhance patient care and operational efficiency. 

What you will do

• Design, develop, and implement machine learning and deep learning models to address hospital-specific challenges such as patient flow optimization, resource allocation, bed management, and predictive analytics for patient outcomes.
• Build and optimize data ingestion and modeling pipelines as needed
• Utilize domain driven techniques and design patterns to build and contribute to technical
• design.
• Collaborate with cross-functional teams including data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions.
• Work with large-scale healthcare and hospital datasets including structured data (EHRs, hospital operational data), unstructured data (clinical notes, imaging).
• Ensure data privacy and security, adhering to healthcare regulations such as HIPAA and GDPR, especially when working with sensitive hospital data.
• Mentor junior engineers and data scientists, providing guidance on machine learning techniques, particularly those relevant to hospitals and healthcare systems.
• Monitor, troubleshoot, and enhance the performance of deployed models using MLOps best practices, ensuring they operate effectively in hospital environments.
• Write technical architectural and design documents.

What we look for

• Proven experience in end-to-end design and deployment of machine learning models from ideation to production in healthcare or similar settings.
• Strong programming skills and experience with object or component-oriented development software, one or more of: Python or R, with proficiency in ML frameworks, one or more of: TensorFlow, PyTorch, or Scikit-learn.
• Expertise in NLP, computer vision, or other specialized machine learning techniques applicable to healthcare and hospital environments.
• Deep knowledge of a scripting or statistical programming language (Python preferred). Ability to efficiently work with very large datasets and deal with non-standard machine learning datasets (class-imbalances, sparse matrices, etc.)
• Assess model performance; train multiple models; carry out tuning.  Run A/B tests on models.
• Comfortable writing complex SQL queries and developing python packages.
• Experience with cloud-based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or Ansible. Interest in developing services as well as the underlying infrastructure
• Experience with database management system software, one or more of: Oracle, MSSQL, MongoDB, MySQL, DynamoDB, or PostgreSQL. 
• Experience with Version Control Software, one or more of: git, Mercurial, CVS, TFS, or Subversion. 
• Strong understanding and experience executing several software development methodologies and life cycles. Ability to understand and translate business requirements into technical specifications.
• Experience with agile development practices.
• Excellent written and oral communication skills. Adept and presenting complex topics, influencing, and executing with timely / actionable follow-through.
• Strong analytical and problem-solving skills with the ability to convert information into practical training deliverables. Uses rigorous logic and methods to solve difficult problems.
• Knowledge of clinical workflows and hospital operations, and how technology can enhance efficiency and patient care.
• Familiarity with healthcare-specific machine learning challenges, such as data imbalance, longitudinal data, and real-time processing in hospital environments.
• Be an active listener, probe requirements for all projects from relevant stakeholders, stay nimble and willing to produce rapid iterations.

Education

• Bachelor's degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 7 or more years of experience.
• Master's or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 5 or more years of experience. (preferred)

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Performance Prediction team builds the Machine Learning models, evaluation pipelines, and internal tools that help us understand how autonomy behavior changes across software releases. We work on problems that span behavior classification, ride quality detection, probabilistic trajectory prediction, and release regression analysis.

Our systems support both classical and modern ML approaches. That includes compact learned classifiers such as tree-based models for behavior and ride quality detection, as well as deep learning-based probabilistic prediction models for more complex autonomy tasks. We also build the software around those models: dataset definition, feature generation, training and tuning workflows, offline metrics, experiment tracking, and tools that help engineers inspect regressions at the slice and scenario level.

This role is a strong fit for someone who enjoys building reliable Python systems and applying rigorous ML evaluation methods in a safety-critical domain. In practice, the work is a mix of ML systems development, model and evaluation work, and internal tooling used by partner teams across autonomy.

What you’ll do: 

• Build production software for model training, offline evaluation, and release-comparison workflows
• Develop and improve learned models for performance prediction, including behavior classifiers and probabilistic prediction models
• Design training, validation, and holdout strategies that produce trustworthy results
• Define and track model and release metrics such as precision, recall, F1, ROC AUC, calibration quality, and task-specific forecasting metrics
• Run experiments, tune models, and analyze results with strong statistical rigor
• Build internal tools that help engineers compare software versions, inspect model outputs, and investigate regressions
• Partner with autonomy, simulation, and infrastructure teams to move ideas from prototype to production
• Raise engineering quality through testing, code review, CI, and maintainable interfaces across data, modeling, and product layers

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong software engineering skills in Python, including experience building modular, maintainable, well-tested systems in a shared codebase
• Experience developing, training, tuning, or productionizing supervised ML models
• Strong grounding in statistics and experimental design, including experience designing model training and evaluation tests
• Experience selecting and interpreting model metrics, thresholds, and tradeoffs for real-world decision-making
• Experience with ML tooling such as PyTorch, scikit-learn, or similar frameworks
• Experience working with large datasets using SQL, pandas, and NumPy
• Strong communication skills and the ability to work effectively across software, ML, and autonomy teams

Nice to have: 

• PhD in Computer Science, Machine Learning, Statistics, Robotics, or a closely related field is preferred
• Equivalent research-heavy industry experience is highly valued
• Experience with probabilistic forecasting, trajectory prediction, sequential modeling, or graph-based models
• Experience with classical ML methods such as random forests, gradient boosting, or calibrated linear models
• Experience with calibration, uncertainty estimation, ablation studies, error analysis, or release regression methodology
• Experience building internal analytics or ML tools with Dash, Plotly, Streamlit, or similar frameworks
• Experience with workflow orchestration or experimentation tools such as Dagster, Airflow, or Weights and Biases
• Experience with Bazel or other large-scale build systems
• Prior autonomous driving experience is helpful but not required. Strong experience with production ML systems and rigorous model evaluation is sufficient

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We’re searching for a Software Engineer II to join the Control Simulation team and help transform how we validate and improve the safety and performance of the Aurora Driver.

In this role, you will operate at the intersection of Machine Learning, Software Engineering, Data Science, and Vehicle Dynamics. You will contribute to the development of our next-generation data driven vehicle simulator, build data pipelines that source critical scenarios from our fleet and generate simulations from logs, and analyze data to prove the safety of our motion control software.

This is a high-impact role for an engineer who enjoys a mix of model development, infrastructure building, and data analysis.

In This Role You Will:

• Develop Vehicle Models: Help design and implement our next-generation differentiable vehicle dynamics simulator for controls V&V.
• Build Simulation Pipelines: Design and maintain the software pipelines required to generate "Sim-from-Log" scenarios. You will ensure that high-value on-road events are systematically converted into reproducible simulation tests.
• Implement Control Scenario Taxonomies & Curate Data: Build the data structures and algorithms to categorize complex control scenarios (e.g., maneuvers, environments) and use this framework to source balanced datasets from on-road logs, ensuring comprehensive ODD coverage for model training.

Required Qualifications:

• BS or MS in Computer Science, Robotics, Data Science, or a related engineering field.
• 2+ years of software engineering experience with a focus on data-intensive applications or machine learning.
• Strong proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn).
• Hands-on experience with PyTorch or similar machine learning frameworks.
• Experience working with large datasets, SQL, and data processing pipelines.
• Strong analytical skills with the ability to translate complex data into actionable engineering insights.
• Background or interest in Control Theory or Vehicle Dynamics (understanding of kinematics, kinetics, and actuation).

Desirable Qualifications:

• Experience with machine learning or system identification for physics based-models.
• Familiarity with V&V methodologies, simulation frameworks, or log analysis tools.
• Experience building data visualization tools or dashboards to track software quality and coverage.
• Proficiency in C++ (necessary for integrating with on-vehicle or production codebases).

The base salary range for this position is $126,000-$181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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