Senior Software Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer, AI/ML Platform based in the United States.

• Design and implement the ML platform that orchestrates the complete AI lifecycle, including data processing, training, evaluation, deployment, and monitoring.
• Develop reliable and scalable workflows across cloud infrastructure, Kubernetes, and continuous automation environments.
• Build foundational ML infrastructure components such as model registries, feature stores, experiment tracking systems, and model management tooling.
• Create developer-facing APIs, command-line tools, and reusable infrastructure that make machine learning workflows simple, reproducible, and accessible to engineering and research teams.
• Implement CI/CD capabilities for ML workflows, supporting continuous retraining, automated testing, standardized model packaging, and reliable production delivery.
• Apply MLOps best practices covering reproducibility, data and model lineage, rollback, monitoring, governance, and operational reliability.
• Partner with ML researchers, robotics engineers, data platform engineers, and other technical stakeholders to translate requirements into scalable infrastructure solutions.
• Integrate ML orchestration and metadata tracking capabilities with existing data lakes, pipelines, and broader platform infrastructure.
• Mentor junior engineers and contribute to architectural decisions, technical standards, and the long-term roadmap for cloud and ML infrastructure.
• Help establish centralized experiment tracking, performance visualization, standardized deployment practices, and post-deployment model monitoring.

• 5+ years of professional software engineering experience, including at least 2+ years building or operating production ML infrastructure, data platforms, or MLOps systems.
• Hands-on experience developing modern ML platform components such as experiment tracking, model registries, training pipelines, deployment systems, or related infrastructure.
• Familiarity with ML orchestration and experiment management technologies such as MLflow, Weights & Biases, Airflow, Kubeflow, or comparable tools.
• Strong experience with cloud-native platforms such as AWS, Google Cloud, or Azure, along with containers and Infrastructure as Code technologies such as Terraform or CDK.
• Experience processing or modeling multimodal datasets, including sensor logs, camera streams, behavioral traces, or similar robotics and machine-learning data.
• Strong software engineering fundamentals and the ability to build reliable, maintainable, production-grade systems.
• Experience collaborating with research scientists, data engineers, robotics teams, or autonomy engineers to deliver infrastructure used by technical teams.
• Strong understanding of CI/CD, automation, observability, reproducibility, and scalable platform architecture.
• Excellent communication and collaboration skills, with the ability to work across disciplines and influence technical decisions.
• Experience with robotics, autonomous vehicles, drones, or embedded machine learning is a plus.
• Contributions to open-source ML infrastructure or MLOps projects are also advantageous.
• Must have current authorization to work in the United States.

• Anticipated base salary of $197,000–$307,000 USD, with final compensation determined by factors such as location, experience, knowledge, and skills.
• Competitive total rewards package for full-time employees.
• 401(k) plan with a 6% company match.
• Company stock options/equity.
• 100% company-paid medical, dental, and vision insurance for employees.
• Company-paid short- and long-term disability insurance.
• Benefits eligibility beginning on the first day of employment.
• Employee Assistance Program (EAP) and well-being support.
• Flexible, unlimited PTO for exempt employees, plus 12 company holidays including a winter shutdown.
• Vacation and paid sick leave for non-exempt employees, plus 12 company holidays including a winter shutdown.
• Generous paid parental leave.
• Flexible work arrangements within a remote-friendly, distributed engineering environment.
• Professional development and tuition reimbursement opportunities.
• Relocation assistance for eligible roles.
• Annual discretionary bonus for eligible roles.
• Catered lunches and snacks at designated office locations.
• Opportunity to work on technically challenging AI, ML, cloud, and robotics infrastructure with significant real-world impact.