Offer summary

Qualifications:

Proven experience with Large Language Models (LLMs) and NLP frameworks like Hugging Face or OpenAI., Strong expertise in AWS Cloud Services such as SageMaker, Lambda, and S3., At least 2 years of leadership experience in ML/AI projects., Hands-on skills in Python, TensorFlow or PyTorch, and model optimization..

Key responsibilities:

Lead and manage a team of 5-10 engineers, providing mentorship.

Design, develop, and fine-tune LLMs and other ML models for business solutions.

Oversee the entire ML lifecycle, including deployment and maintenance.

Coordinate cross-functional efforts to ensure project delivery.

Job description

Provectus helps companies adopt MLAI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive endtoend AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organizationwide 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 cuttingedge AI solutions while managing a team of 510 engineers. This leadership role demands handson technical expertise, strategic planning, and team management capabilities to deliver innovative products at scale.

Responsibilities:Leadership & Management
Lead and manage a team of 510 engineers, providing mentorship and fostering a collaborative team environment;
Drive the roadmap for machine learning projects aligned with business goals;
Coordinate crossfunctional efforts with product, data, and engineering teams to ensure seamless delivery.
Machine Learning & LLM Expertise
Design, develop, and finetune LLMs and other machine learning models to solve business problems;
Evaluate and implement stateoftheart 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 costefficiency 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 CICD 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 MLAI, including at least 2 years in a leadership role;
Handson experience with Python, TensorFlowPyTorch, and model optimization;
Familiarity with MLOps tools and best practices;
Excellent problemsolving and decisionmaking abilities;
Strong communication skills and the ability to lead crossfunctional teams;
Passion for mentoring and developing engineers.