Senior Software Engineer

Compunnel, Inc.; Westbrook (ME); On-site; USD 120,000 - 160,000; Full time

Job summary

Compunnel, Inc. is seeking an experienced Machine Learning Engineer to join the MLOps team in the R&D AI Center of Excellence. You will build and operate pipelines that turn Data Scientists' models into production systems, covering training, inference, and edge deployment on specialized hardware.

Collaborate with data scientists and software engineers to optimize models, implement IaC for ML platforms, and stay ahead of advances in ML, computer vision, and edge AI.

Qualifications

• Experience delivering solutions into production.
• Excellent software engineering skills with a test-driven mindset.
• Strong programming skills in Python and Spark.
• Experience with distributed computing frameworks such as Ray and ML frameworks like PyTorch.
• Experience with ML stacks including Databricks, MLflow, AWS, Docker, and IaC tools.

Responsibilities

• Partner with Data Scientists to productionize ML and CV models with scalable training and inference pipelines.
• Optimize models for performance and edge deployment (TensorRT, CUDA).
• Integrate ML models into production systems on cloud and at the edge.
• Collaborate to identify data requirements and build preprocessing pipelines.
• Maintain infrastructure-as-code for ML platforms and deployments.
• Stay updated with ML, CV, and MLOps advances.

Skills

Python

Spark

Distributed computing (Ray)

Problem-solving

Communication

Tools

Databricks

MLflow

AWS (EC2/S3/Lambda)

Docker

Terraform

CloudFormation

TensorRT

NVIDIA Jetson/DeepStream

Nsight

Job description

We are seeking an experienced Machine Learning Engineer to join the Machine Learning Operations team in Client's R&D AI Center of Excellence. In this role, you will build and operate the infrastructure that turns Data Scientists' models into production systems - from scalable training and inference pipelines to optimized on-device deployment on edge hardware. The Machine Learning Operations team supports all projects in the Center of Excellence, including Client's inVue Dx's computer vision and microscopy-based diagnostics, and you will contribute to high impact problems.

Job Description:

• Partner with Data Scientists to productionize machine learning and computer vision models, and implement scalable, efficient training and inference pipelines
• Optimize models for performance and scalability, including GPU/CUDA-level tuning and edge/embedded inference optimization (e.g., TensorRT, DLA)
• Work with software engineers and Data Scientists to integrate ML models into production systems on the cloud and at the edge
• Collaborate with Data Scientists to identify and analyze data requirements
• Develop and implement data preprocessing and feature engineering pipelines
• Build and maintain infrastructure-as-code for ML platforms and deployments
• Stay up to date with the latest developments in machine learning, computer vision, and MLOps

Required Skillsets:

• Previous experience in machine learning as evidenced by delivering solutions into production
• Excellent software engineering skills including a test-driven mindset
• Strong programming skills in Python and Spark
• Experience with distributed computing frameworks such as Ray, and ML frameworks such as PyTorch and modern foundation/vision models
• Experience with ML tech stacks, including Databricks (including Databricks Asset Bundles), MLflow, Amazon AWS (EC2, S3, Lambda), containerization technologies such as Docker, and infrastructure-as-code tools including Terraform and CloudFormation
• Experience optimizing and deploying models for GPU or edge inference (CUDA, TensorRT); familiarity with NVIDIA edge platforms (Jetson Orin/Thor) and tooling (Nsight, DeepStream SDK) a plus
• Familiarity with computer vision and/or microscopy/scientific imaging data a plus
• Experience creating and deploying applications to AWS Lambda
• High level of comfort with Linux
• Experience with SQL
• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills