Sr. AI​/ML Engineer -Remote

Title:

Sr. AI/ML Engineer
Location :
Plymouth, MA (Open to 100% Remote)
Target Start Date : 2/10/2026
Type: (C, CTH,

D) D
Pay Rate / Salary (Ranges OK) : $125,000-$165,000

Job Description :

Overview
We are seeking a Senior Data Scientist to build and deploy production-ready machine learning and generative AI solutions. This role focuses on developing intelligent systems using LLMs, agent-based architectures, and scalable MLOps practices.

Key Responsibilities

• Build, deploy, and optimize ML and generative AI solutions in production

• Develop Retrieval Augmented Generation (RAG) pipelines and AI agents

• Implement agent orchestration patterns (MCP, A2A) using Lang Chain and Lang Graph

• Design MLOps pipelines for model training, deployment, monitoring, and feedback loops

• Collaborate with data engineering teams on data pipelines and features

• Mentor junior data scientists and contribute to AI best practices

Required Experience

• 5 years in data science or machine learning

• Strong experience with LLMs, generative AI, and prompt/context engineering

• Hands-on RAG and vector database experience

• Proficiency in Python, PyTorch and/or Tensor Flow

• Solid MLOps experience (CI/CD, model versioning, monitoring)

• Experience deploying models on cloud platforms (AWS, Azure, or GCP)

• Strong communication and stakeholder engagement skills

Preferred Experience

• Regulated industry experience (finance, healthcare)

• Experience with OpenAI / Anthropic APIs

• Vector databases (Pinecone, Weaviate, Chroma)

• Large-scale or distributed model deployment

• Open-source ML/AI contributions

Tech Stack
Python, SQL
• PyTorch, Tensor Flow, scikit-learn
• Lang Chain, Lang Graph, Hugging Face
Docker, Kubernetes, MLflow
• AWS / Azure / GCP
• Vector databases

Bonus/Soft Skills :

• The team values adaptability, eagerness to learn, and excitement about AI/ML and GenAI.
• Company culture is collaborative and fast-paced, with a focus on innovation.
• The team is currently using Snowflake and Azure, with professional services support for MLOps setup.