AI/ML Engineer

Role: AI/ML Engineer
Remote position
Longterm contract
Experience: 5+ years

Interview face to face (1 round) - New York, NY, or Malvern, PA, or Charlotte, NC

Key Responsibilities

• Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving.

• LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems.

• Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock, to build scalable and efficient solutions.

• MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration.

• Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality.

• Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact.

• Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features.

Required Qualifications

• Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.

• Education: Master s degree in Computer Science, Data Science, Engineering, or a quantitative field.
• Technical Proficiency:

• Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn).

• Proven experience in deploying models on major cloud platforms (Google Cloud Platform, AWS, or Azure).

• Deep understanding of the architecture and fine-tuning of Large Language Models.

• Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval).

• Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions.

Preferred Qualifications

• Hands-on experience developing applications or services using Google's Gemini API or models.

• Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock.

• Experience in building and managing multi-step, reasoning-based Agentic AI systems.

• Prior experience in optimizing models for latency and cost efficiency in a production environment.