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Job Description: Machine Learning Tech Lead (with GenAI, AWS)- job post
Provectus
4.5
4.5 out of 5 stars
Maine•Remote
Full-time
Provectus
Maine•Remote

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Profile insights
Here’s how the job qualifications align with your profile.
Skills

TensorFlow
 (Required)

PyTorch
 (Required)

Natural language processing
 (Required)

MLOps
 (Required)

Python
 (Required)

Leadership
 (Required)

AI
 (Required)

Strategic planning

NER

Model deployment

Management

Machine learning

Communication skills

Cloud infrastructure

Cloud architecture

CI/CD

Team management

S3

AWS
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Job details
Here’s how the job details align with your profile.
Job type

Full-time
 
Full job description
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.
 
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