Lead Machine Learning Engineer

Job Description

SilverlineIT is looking for a Lead Machine Learning Engineer to join our innovative tech team.

Duties & Responsibilities

• Design, develop, and deploy end-to-end machine learning models and pipelines for production environments.
• Lead the full ML lifecycle — from data ingestion and feature engineering to model training, evaluation, and monitoring.
• Collaborate with cross-functional teams including product, engineering, and data teams to define ML requirements and deliver scalable solutions.
• Architect and maintain ML infrastructure using cloud-based platforms such as AWS, GCP, or Azure.
• Research and evaluate state-of-the-art ML techniques, frameworks, and tools to continuously improve model performance.
• Mentor and guide junior ML engineers, contributing to overall team capability development.
• Establish best practices for model versioning, testing, documentation, and deployment.
• Present findings, progress, and technical strategies to both technical and non-technical stakeholders.

Our Requirements

• Must be able to work between 8:00 AM – 5:00 PM Eastern Time Zone (ET).
• Strong communication skills in English and the ability to collaborate effectively across teams are essential.
• 3–5 years of hands-on experience in machine learning, data science, or a related field.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Hands-on expertise with Large Language Models (LLMs), including fine-tuning, prompt engineering, and model evaluation.
• Solid experience building Retrieval-Augmented Generation (RAG) pipelines and integrating them into production applications.
• Practical knowledge of agentic AI frameworks and multi-agent system design (e.g. LangChain, LangGraph, AutoGen, or similar).
• Experience working with vector databases such as Pinecone, Weaviate, Qdrant, or pgvector.
• Familiarity with MLOps practices — model versioning, CI/CD pipelines, and automated retraining workflows.
• Experience with cloud platforms such as AWS SageMaker, GCP Vertex AI, or Azure ML.
• Strong understanding of data structures, algorithms, and statistical modelling.
• Experience with tools such as MLflow, Kubeflow, Docker, or Kubernetes is an advantage.
• Demonstrated ability to lead technical projects and mentor team members.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related discipline.

What You’ll Receive

• Competitive compensation package aligned with experience and market benchmarks.
• Direct onboarding with a reputable US-based company.
• Fully remote work environment with flexible tooling and resources.
• Opportunity to work on cutting-edge AI/ML products with a high-impact global team.
• Professional development support and exposure to an international client base.
• Collaborative and growth-oriented team culture.

If you have strong expertise in building scalable ML models, leading AI projects, and turning data into impactful solutions, this is your chance to work remotely, enjoy great benefits, and grow your future with us.