Senior Software Engineer, Production Pipelines

Mindspan Institute; Cambridge (MA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Health Insurance

Dental Insurance

Vision Insurance

Family Benefits

Matching Retirement Contribution

Job summary

Mindspan Institute in Cambridge, MA is seeking engineers to productionize research models as versioned, tested inference services and batch jobs, and to build reliable distributed inference pipelines for very large image volumes.

The role will own automated training, evaluation, monitoring, and release processes, and document systems to keep them usable by scientists, ensuring robust performance and reproducibility across experiments.

Qualifications

• Requires at least five years building and operating production software.
• Experience running machine learning models in production.
• Hands-on experience with distributed systems and Python.
• Experience with containers, workflow orchestration, and infrastructure as code.

Responsibilities

• Productionize research models as versioned, tested inference services and batch jobs.
• Own automated training, evaluation, monitoring, and release processes.
• Document systems to keep them usable by scientists.

Skills

Python

Production Software Engineering

Machine Learning Operations

Distributed Inference

Batch Processing

GPU Inference Optimization

Tools

Kubernetes

SLURM

Ray

Dask

Spark

Containerization

Workflow Orchestration

Infrastructure as Code

CI/CD

Model Evaluation and Release

Job description

Productionize research models as versioned, tested inference services and batch jobs, and build reliable distributed inference pipelines for very large image volumes. Own the automated training, evaluation, monitoring, and release processes, while documenting systems and making them usable by scientists.

Requirements

Requires at least five years building and operating production software, including experience running machine learning models in production, strong Python and software engineering practices, and hands-on experience with distributed systems. Candidates should also have experience with containers, workflow orchestration, infrastructure as code, and deploying and optimizing GPU inference; scientific research experience is not required.

Key Skills

• Python
• Production Software Engineering
• Machine Learning Operations
• Distributed Inference
• Batch Processing
• GPU Inference Optimization
• Kubernetes
• SLURM
• Ray
• Dask
• Spark
• Containerization
• Workflow Orchestration
• Infrastructure as Code
• CI/CD
• Model Evaluation and Release

Benefits

• Health Insurance
• Dental Insurance
• Vision Insurance
• Family Benefits
• Matching Retirement Contribution