Machine Learning Engineer

Could you be a good fit?

We are looking for a highly skilled Machine Learning Engineer to join the team of our exceptional client. This role focuses on building and operating the infrastructure that transforms machine learning and computer vision models into scalable production systems. You''ll work closely with Data Scientists and Software Engineers to develop robust training and inference pipelines, optimize model performance, and support cutting-edge AI solutions deployed in both cloud and edge environments.

Benefits:

• Hybrid work environment (Greater Portland Maine area preferred)
• Healthcare Medical, Dental, and Vision Insurance
• 401(k)

What will your day look like? As a Machine Learning Engineer, you will:

• 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 using technologies such as TensorRT and DLA
• Collaborate with Software Engineers and Data Scientists to integrate machine learning models into production systems in cloud and edge environments
• Analyze data requirements and support the development of data-driven solutions
• Design and implement data preprocessing and feature engineering pipelines
• Build and maintain infrastructure-as-code for machine learning platforms and deployments
• Develop, deploy, and support machine learning applications using modern MLOps tools and frameworks
• Stay current with emerging technologies and best practices in machine learning, computer vision, and MLOps
• Contribute to high-impact AI initiatives while helping drive operational excellence across machine learning projects

You will be a good fit for the Machine Learning Engineer role if you have:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience)
• Proven experience delivering machine learning solutions into production environments
• Strong software engineering skills with a test-driven development mindset
• Advanced programming experience with Python and experience working with Spark
• Hands-on experience with distributed computing frameworks such as Ray
• Experience with machine learning frameworks such as PyTorch and modern foundation and vision models
• Strong knowledge of MLOps technologies including Databricks, Databricks Asset Bundles, MLflow, and AWS services such as EC2, S3, and Lambda
• Experience with containerization technologies such as Docker
• Experience using infrastructure-as-code tools including Terraform and CloudFormation
• Expertise optimizing and deploying models for GPU and edge inference using technologies such as CUDA and TensorRT
• Experience creating and deploying applications to AWS Lambda
• Strong Linux administration and troubleshooting skills
• Experience writing and optimizing SQL queries
• Excellent problem-solving, analytical, communication, and collaboration skills

Nice-to-Haves:

• Experience with NVIDIA edge platforms such as Jetson Orin or Thor
• Familiarity with NVIDIA development and optimization tools including Nsight and DeepStream SDK
• Experience working with computer vision applications
• Familiarity with microscopy, scientific imaging, or other image-intensive data domains
• Experience supporting enterprise-scale machine learning operations and AI platforms

About Market Street Talent

We are a specialized staffing and consulting firm focused on IT and technology positions. Our deep industry knowledge allows us to match exceptional candidates with organizations where they can thrive and make an immediate impact.

Our Vision: To promote and foster the growth of information technology (IT) in our world—one candidate, one client, one community at a time.

Our Goal: To guide clients and candidates through the placement process and build long-term, successful relationships.

Our Culture: At MST, we value excellence, respect, and empathy in everything we do.

Sound like you? Ready for your next challenging IT opportunity? Click "Apply Now!"