Machine Learning Tech Lead

Summary

Join Provectus, a company focused on ML/AI adoption, as a Machine Learning Tech Lead specializing in Large Language Models (LLMs) and AWS Cloud services. You will lead and mentor a team of 5-10 engineers, driving the development and deployment of cutting-edge AI solutions. This role demands hands-on technical expertise, strategic planning, and strong team management skills. Responsibilities include designing, developing, and fine-tuning LLMs, architecting scalable ML solutions on AWS, and overseeing the entire ML lifecycle. You will also foster a collaborative team environment and ensure engineering standards are upheld. The ideal candidate possesses extensive experience with LLMs, AWS, and ML/AI, including leadership experience.

Requirements

• Proven experience with LLMs and NLP frameworks (e.g., Hugging Face, OpenAI, or Anthropic models)
• Strong expertise in AWS Cloud Services
• Strong experience in ML/AI, including at least 2 years in a leadership role
• Hands-on experience with Python, TensorFlow/PyTorch, and model optimization
• Familiarity with MLOps tools and best practices
• Excellent problem-solving and decision-making abilities
• Strong communication skills and the ability to lead cross-functional teams
• Passion for mentoring and developing engineers

Responsibilities

• Lead and manage a team of 5-10 engineers, providing mentorship and fostering a collaborative team environment
• Drive the roadmap for machine learning projects aligned with business goals
• Coordinate cross-functional efforts with product, data, and engineering teams to ensure seamless delivery
• Design, develop, and fine-tune LLMs and other machine learning models to solve business problems
• Evaluate and implement state-of-the-art LLM techniques for NLP tasks such as text generation, summarization, and entity extraction
• Stay ahead of advancements in LLMs and apply emerging technologies
• Expertise in multiple main fields of ML: NLP, Computer Vision, RL, deep learning and classical ML
• Architect and manage scalable ML solutions using AWS services (e.g., SageMaker, Lambda, Bedrock, S3, ECS, ECR, etc.)
• Optimize models and data pipelines for performance, scalability, and cost-efficiency in AWS
• Ensure best practices in security, monitoring, and compliance within the cloud infrastructure
• Oversee the entire ML lifecycle, from research and experimentation to production and maintenance
• Implement MLOps and LLMOps practices to streamline model deployment and CI/CD workflows
• Debug, troubleshoot, and optimize production ML models for performance
• Conduct regular code reviews and ensure engineering standards are upheld
• Facilitate professional growth and learning for the team through continuous feedback and guidance
• Communicate progress, challenges, and solutions to stakeholders and senior leadership

Benefits

• Sing-up bonus 8,000 USD
• Long-term B2B collaboration
• Fully remote setup
• Comprehensive private medical insurance or budget for your medical needs
• Paid sick leave, vacation, public holidays
• Continuous learning support, including unlimited AWS certification sponsorship