Lead ML Engineer

Machine Learning Technologies, LLC; Atlanta (GA); On-site; USD 140,000 - 210,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a highly skilled Machine Learning Engineer with 8+ years of experience to join our AI team in a hands-on role bridging cutting-edge research and production.

You will design, build, and deploy Generative AI models (LLMs and diffusion techniques) and translate complex AI concepts for non-technical stakeholders while collaborating with product managers and engineers.

Qualifications

• 10+ years of ML Engineer experience, with 1–2 years in Generative AI/NLP.
• Strong Python proficiency and cloud experience (AWS).
• Experience deploying GenAI models and building scalable ML pipelines.

Responsibilities

• Architect, fine-tune, and deploy LLMs and GenAI techniques.
• Build scalable ML pipelines and GPU-based inference in cloud environments.
• Translate AI concepts to non-technical stakeholders and leadership.
• Collaborate with product managers and engineers to meet business needs.
• Stay updated with GenAI research and apply to production systems.

Skills

10+ years ML Engineer experience

Python proficiency

GenAI & NLP

Communication

Problem solving

Cross-functional collaboration

Education

Engineering degree in computer science or equivalent

Tools

Docker

Kubernetes

CI/CD for ML

AWS services (SageMaker, Bedrock)

GitHub Copilot

Job description

Work Authorization:

We are seeking a highly skilled and communicative Machine Learning Engineer (8+ years of experience) to join our AI team.

In this role, you will bridge the gap between cutting-edge AI research and practical, user-facing applications.

You will be responsible for designing, building, and deploying Generative AI models (LLMs, Diffusion Models) to solve complex business problems, while effectively communicating technical advancements to non-technical stakeholders.

The ideal candidate is both a hands-on coder passionate about ML, Gen AI and a proactive collaborator who excels at explaining complex AI concepts to diverse teams.

Key Responsibilities

• GenAI Development:Architect, fine-tune, and deploy Large Language Models (LLMs) and Generative AI techniques (e.g., RAG, PEFT/SFT) to improve business applications.
• Production Deployment:Build and maintain high-performance, scalable ML pipelines and GPU-based inference systems in cloud environments (AWS/GCP/Azure).
• Collaboration & Communication:Work closely with product managers, data scientists, and engineers to translate business requirements into technical specifications.
• Stakeholder Engagement:Clearly present AI methodologies, performance results, and technical trade-offs to non-technical stakeholders and leadership.
• Model Optimization:Implement prompt engineering, adversarial testing, and model optimization strategies to ensure high-quality, efficient, and safe outputs.
• Stay Updated:Actively keep up with the latest advancements in GenAI research and incorporate them into our production systems.
• Team and project Coordination:Define project scope, timelines, deliverables, success metrics, co-ordinate with and guide offshore technical team on project deliverables.

Required Skills & Qualifications

• Experience:10+ years of experience as an ML Engineer, with at least 1-2 years dedicated to Generative AI or NLP projects, and good experience on AWS cloud platform.
• Technical Expertise:Strong proficiency in Python, and IDEs such as Cursor/AWS Kiro, deep learning frameworks (PyTorch or TensorFlow or), utilizing GitHub co-pilot etc.
• GenAI Proficiency:Hands-on experience with LLMs (e.g., GPT-4, Llama), RAG architectures, LangChain, Vector Databases, Knowledge graphs, and Agentic AI
• MLOps and LLM Ops:Familiarity with Docker, Kubernetes, and CI/CD tools for ML.
• AWS Skills:S3, Lambda, Glue, AWS Sage maker, and AWS Bedrock platform
• Communication Skills:Excellentverbal and written communication skills; ability to articulate complex technical concepts simply.
• Stakeholder Management:Able to collaborate with key business/client stakeholders and manage their expectations
• Problem-Solving:Proven ability to work independently in a fast-paced environment and troubleshoot issues.

Preferred Qualifications

• Engineering degree in computer science or equivalent, and relevant certification in Machine learning
• Experience in banking or financial services domain – Payments industry.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.