Senior ML Ops Engineer — Edge & Cloud Pipelines

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

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.