Senior Software Engineer, AI/ML Platform
Agility Robotics is hiring a Senior Software Engineer, AI/ML Platform for a remote role open to applicants in United States. It pays $197k-$307k a year and Level rates it ; you can apply on Agility Robotics.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 18% above the typical software engineer posting on Level.
- The posting lists this role as remote.
- Tools and skills the posting cites include MLflow, Weights And Biases and Kubernetes.
- Level lists 78 other open roles at Agility Robotics.
AI in this role
Build foundational ML platform infrastructure and orchestration pipelines for fleet-scale humanoid robotics.
Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.
About The RoleJoin the team building the machine learning platform to power fleet-scale humanoid robotics. As a senior engineer on the ML Infrastructure and Platform group, you will help architect and build the foundational infrastructure for AI and machine learning operations at Agility. This includes the platform layer for data collection and processing, training, sim and real evaluation, and model management and observability.
Your work will empower our AI teams across perception, controls, skills, and innovation to build and deploy next-generation robot foundation models and end-to-end policies for humanoid robots by providing tools to develop and operationalize machine learning at scale.
Key Responsibilities
Execution and Technical Ownership
- Contribute to the design and implementation of the ML platform for orchestrating the end to end AI flywheel of data processing, training, evaluation, and deployment
- Develop reliable workflows across cloud compute, Kubernetes, and continuous automation
- Build core infrastructure components such as the model registry, feature store and experiment tracking tooling.
- Own developer-facing APIs and CLI tools that make ML workflows simple and reproducible.
- Implement the CI/CD lifecycle for ML that enable continuous retraining, automated testing, and seamless model delivery to production environments
Collaboration
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- Work closely with the Staff ML Infra Engineer and cross-functional stakeholders (AI researchers and robotics engineers) to understand requirements and translate them into scalable solutions/systems.
- Partner with data platform engineers to integrate ML orchestration and metadata tracking tools with our existing data lake and pipelines.
Engineering Excellence, Growth and Impact:
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- Apply MLOps best practices: reproducibility, lineage, rollback, monitoring and governance.
- Mentor junior engineers and influence the broader cloud platform organization’s roadmap.
- Contribute to internal discussions on platform architecture, reliability, and scalability alongside the broader ML and data platform team
What We’re Aiming For (MLOps Level 2)
- Version-controlled ML pipelines (data, code, and config)
- Automated and reproducible model training and evaluation
- Continuous integration and delivery for ML workflows
- Centralized experiment tracking and performance visualization
- Standardized model packaging and deployment to production
- Monitoring of models post-deployment
Required Qualifications
- 5+ years of software engineering experience, with at least 2+ years working on ML infrastructure, data platforms or MLOps systems in production environments.
- Experience building and maintaining components of modern ML platforms—such as experiment tracking, model registries, training pipelines, or deployment systems
- Familiarity with orchestration and tracking tools (MLflow, WandB, Airflow, Kubeflow, etc.)
- Proficiency with cloud-native platforms (AWS, GCP, or Azure), containers, and IaC (e.g., CDK, Terraform)
- Hands-on experience with processing or modeling multimodal data(sensor logs, camera streams, behaviour traces etc).
- Comfortable collaborating cross-functionally with research scientists, data engineers, and robotics/autonomy teams to ship infrastructure used by others
Bonus Qualifications
- Experience with robotics, autonomous vehicles, drones or embedded ML.
- Contributions to open-source ML infrastructure or MLOps tooling a plus.
Why This Role?
- Build from the start Join at a pivotal moment - help shape the ML platform layer as its being defined, not inherited.
- High impact: Your work will directly enable faster, safer, and more intelligent robotic behaviors at scale
- Technical Frontier: You will work directly on enabling the next frontier of AI in real production settings
- Remote-friendly with a strong engineering culture and a fully distributed team.
The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.
Anticipated Base Salary Range$197,000—$307,000 USDIn addition to base pay, our competitive total rewards package consists of the following for full-time employees:
- 401(k) Plan: Includes a 6% company match.
- Equity: Company stock options.
- Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
- Benefit Start Date: Eligible for benefits on your first day of employment.
- Well-Being Support: Employee Assistance Program (EAP).
- Time Off:
- Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
- Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
- On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
- Parental Leave: Generous paid parental leave programs.
- Work Environment: A culture that supports flexible work arrangements.
- Growth Opportunities: Professional development and tuition reimbursement programs.
- Relocation Assistance: Provided for eligible roles.
- Annual Discretionary Bonus: Provided for eligible roles.
All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.
Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.
Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.
How we rate this
Senior Software Engineer, AI/ML Platform at Agility Robotics rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $197k
- Typical software engineer job
- $167k
This posting starts 18% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where mlops was part of your work. What did you do?
- Tell me about a project where machine learning platform was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where ci/cd was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, MLOps, Machine Learning Platform, Infrastructure, and CI/CD. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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