Senior Machine Learning Engineer

Regenerativeaitool; Boston (MA); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Comprehensive health, dental, and vision insurance

Flexible PTO and remote-friendly work arrangements

Annual learning and development budget ($5,000)

Home office setup allowance

401(k) with company match

Job summary

Regenerative AI in Boston is seeking a Senior Machine Learning Engineer to design and operate production ML systems with feedback loops. You will work on building and maintaining self-adaptive ML systems with monitoring and recalibration features.

Ideal candidates will have over 5 years of experience in ML systems and expertise in Python and modern frameworks. The position offers competitive salary, health benefits, and a flexible work environment.

Qualifications

• 5+ years of experience building and deploying ML systems in production environments.
• Strong proficiency in Python and modern ML frameworks.
• Hands-on experience with distributed training and GPU infrastructure.

Responsibilities

• Design and implement end-to-end ML pipelines: data ingestion, training, evaluation, and serving.
• Build and maintain self-adaptive ML systems with runtime monitoring and drift detection.
• Develop automated recalibration workflows that respond to performance degradation.

Skills

Python proficiency

ML frameworks (PyTorch, TensorFlow, or JAX)

Distributed training

MLOps practices

Monitoring tools (Prometheus, Grafana, Datadog)

Data pipelines (Kafka, Spark, Airflow)

Software engineering fundamentals

Tools

Kubernetes

Docker

Cloud-native ML infrastructure

Job description

Regenerative AI builds self-adaptive AI systems that continuously monitor, regulate, and improve their own behavior during real-world operation. We are looking for a Senior Machine Learning Engineer to join our ML Systems team in Boston. You will design, build, and operate production ML systems with built-in feedback loops, runtime monitoring, and automated recalibration. This is a hands-on engineering role focused on system-level robustness, reliability, and continuous adaptation in deployment.

What You'll Do

• Design and implement end-to-end ML pipelines: data ingestion, training, evaluation, and serving
• Build and maintain self-adaptive ML systems with runtime monitoring and drift detection
• Develop automated recalibration workflows that respond to performance degradation
• Create observability infrastructure for model health, latency, and prediction quality
• Own incident response and reliability for ML services in production
• Collaborate with platform engineers to integrate ML workloads into CI/CD pipelines
• Establish and enforce governance standards for model versioning, rollback, and auditability
• Optimize training and inference infrastructure for efficiency and cost
• Contribute to internal tooling that accelerates ML development velocity

Qualifications

• 5+ years of experience building and deploying ML systems in production environments
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX)
• Hands-on experience with distributed training and GPU infrastructure
• Deep understanding of MLOps practices: CI/CD for ML, model versioning, feature stores
• Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, or similar)
• Solid understanding of data pipelines and streaming systems (Kafka, Spark, Airflow)
• Track record of owning and operating ML services with high availability requirements
• Strong software engineering fundamentals and code quality standards

Nice to Have

• Experience with online learning, adaptive models, or feedback-driven systems
• Background in model monitoring, drift detection, or anomaly detection
• Familiarity with control systems concepts or adaptive control
• Experience with Kubernetes, Docker, and cloud-native ML infrastructure
• Knowledge of reliability engineering practices (SLOs, error budgets, on-call)
• Experience building internal ML platforms or developer tools

Competitive salary and meaningful equity

Comprehensive health, dental, and vision insurance

Flexible PTO and remote-friendly work arrangements

Annual learning and development budget ($5,000)

Home office setup allowance

401(k) with company match

Ready to Join Us?

We're excited to learn more about you. Apply now and take the next step in your career with Regenerative AI.