Machine Learning Tech Lead

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. We are seeking a highly skilled Machine Learning (ML) Tech Lead with a strong background in Large Language Models (LLMs) and AWS Cloud services. The ideal candidate will oversee the development and deployment of cutting-edge AI solutions while managing a team of 5-10 engineers. This leadership role demands hands-on technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale. Responsibilities: Leadership & Management -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. Machine Learning & LLM Expertise -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. AWS Cloud Expertise -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. Technical Execution -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. Team Development & Communication -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. Qualifications: 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. What We Offer: Sing-up bonus 7,000 USD; Long-term B2B collaboration; Fully remote setup; Comprehensive private medical insuranceor budget for your medical needs; Paid sick leave, vacation, public holidays; Continuous learning support, including unlimited AWS certification sponsorship.