Senior Software Engineer - ML Infrastructure

Location: Pittsburgh, PA; Palo Alto, CA; Detroit, MI; remote. Candidates must be legally authorized to work in the United States on a permanent basis. Visa sponsorship is available.

Expected base salary in California: $179,200–$268,800 USD annually. Actual pay depends on work location, experience, education, training, and skills. Annual bonuses and equity compensation are also available.

Company

hirify.global, a Ford Motor Company subsidiary operating with a technology-startup approach, develops hands-free automated driving and advanced driver assistance technology.

What you will do

• Curate balanced, high-quality training and evaluation datasets from real-world and simulated driving data.
• Design scalable, reproducible data pipelines with versioning, provenance, data contracts, and train/validation/holdout splits.
• Analyze dataset coverage, label quality, scenario behavior, and software-release changes to guide autonomy priorities.
• Build and scale training, inference, evaluation, experiment-tracking, and automated analytics pipelines.
• Train, tune, productionize, and integrate learned models ranging from classical methods to deep learning.
• Define and validate model and release metrics, run experiments, build dashboards and services, and collaborate with autonomy, simulation, data, and infrastructure teams.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field plus 4+ years of relevant industry experience, or a master’s degree plus 2+ years of relevant experience.
• Strong Python software engineering skills, including modular, maintainable, well-tested systems in a shared codebase.
• Experience building end-to-end ML systems from data pipelines and dataset curation through training, evaluation, and production, using tools such as SQL, pandas, PyTorch, or scikit-learn.
• Experience designing scalable ML infrastructure, including training and evaluation pipelines, experiment tracking, model serving, or distributed jobs.
• Solid knowledge of statistics and experimental design, including evaluation strategies, metrics, and thresholds for real-world decisions.
• Clear communication and effective collaboration across software, ML, and autonomy teams.

Nice to have

• Experience with probabilistic forecasting, sequential or graph-based models, and classical methods such as gradient boosting.
• Experience with calibration, uncertainty estimation, ablation studies, error analysis, or release-over-release comparison.
• Experience with data-centric ML, including active learning, auto-labeling, embedding-based search, or dataset versioning.
• Experience with Dagster, Airflow, Ray, Weights & Biases, Dash, Streamlit, or similar orchestration, experimentation, and internal tooling.
• Experience with Bazel or other large-scale build systems.
• Autonomous driving or robotics experience.

Culture & Benefits

• Remote work and office locations in Pittsburgh, Palo Alto, and Detroit.
• Medical, dental, and vision insurance for employees and families, plus a health savings account with employer match.
• Employer-matched 401(k) with immediate vesting, life insurance, paid medical and parental leave, and adoption or surrogacy support.
• Unlimited vacation, 15 paid holidays, commuter and dependent-care benefits, and a monthly wellness stipend.
• Professional development reimbursement, backup child and elder care, employee assistance, and additional discounted protection programs.
• Daily office lunches and refreshments, employee resource groups, team activity stipends, and wellness initiatives.