Machine Learning Tech Lead, (with GenAI)

Machine Learning Tech Lead, (with GenAI)

Machine Learning Tech Lead, (with GenAI)

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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 :

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Engineering and Information Technology

Industries

Hospitality, Food and Beverage Services, and Retail

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