8+ years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.
Master's degree in Computer Science, Data Science, Engineering, or a quantitative field.
Proficiency in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
Experience deploying models on major cloud platforms (GCP, AWS, or Azure) and deep understanding of Large Language Models.
Requirements:
Full ML lifecycle management from ideation to production deployment, including data pipeline development, model training, validation, and serving.
Design and optimize solutions utilizing Large Language Models (LLMs) and developing Agentic AI systems.
Leverage core generative AI platforms (e.g., Gemini and Amazon Bedrock) to build scalable and efficient solutions.
Implement MLOps practices using tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration.
Job description
Location: Remote. Position : Data Scientists Salary range: 130k- $150k/Year
🤖 AI/ML Lead Engineer (8+ yrs Years Experience) 📌 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: 8+ 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 (GCP, 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.
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.
