Lead ML Engineer

Ethereum Technologies; Atlanta (GA); On-site; USD 180,000 - 260,000; Full time

Job summary

Ethereum Technologies is seeking a highly skilled Machine Learning Engineer (8+ years) to bridge cutting-edge GenAI research with practical user-facing applications. You will design, build, and deploy Generative AI models (LLMs, diffusion models) to solve complex business problems and communicate technical advancements to non-technical stakeholders.

The role emphasizes hands-on coding, collaboration across product teams, and leadership in optimizing ML pipelines in cloud environments.

Qualifications

• 10+ years of experience as an ML Engineer, with 1-2 years in Generative AI or NLP projects.
• Strong proficiency in Python and ML frameworks; experience on AWS.
• Hands-on with LLMs (GPT-4, Llama), RAG, LangChain, vector DBs, knowledge graphs, and Agentic AI.

Responsibilities

• Architect, fine-tune, and deploy LLMs and GenAI techniques to improve business applications.
• Build and maintain scalable ML pipelines and GPU-based inference in cloud environments (AWS/GCP/Azure).
• Collaborate with PMs, data scientists, and engineers to translate requirements into specs.
• Present AI methodologies and results to non-technical stakeholders and leadership.
• Implement prompt engineering, adversarial testing, and model optimization for quality and safety.
• Stay updated with GenAI research and apply to production systems.
• Coordinate with offshore team on project deliverables.

Skills

Python

AWS

LLMs

NLP

PyTorch

TensorFlow

LangChain

Vector Databases

Knowledge graphs

Docker

Kubernetes

CI/CD

GitHub Copilot

Education

Engineering degree in computer science

Machine learning certification

Tools

Docker

Kubernetes

AWS SageMaker

AWS Bedrock

S3

Lambda

Glue

Job description

Client:

To Be Discussed Later

Employment Type:

W-2, 1099, C2C

Work Authorization:

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

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.