ML engineer with Gen AI

Ethereum Technologies; Austin (TX); On-site; USD 180,000 - 250,000; Full time

Job summary

Ethereum Technologies is seeking a senior ML engineer to architect, fine-tune, and deploy generative AI models, supporting large-scale business applications. You will build scalable ML pipelines on AWS, collaborate with product managers and data scientists, and translate complex requirements into robust technical specs.

You will demonstrate hands-on experience with LLMs and RAG, implement MLOps practices, and clearly communicate results to leadership while staying current with GenAI research and

Qualifications

• Experience: 10+ years as ML Engineer, with 1-2 years Generative AI or NLP, and AWS experience.
• Technical Expertise: Python proficiency and IDEs such as Cursor/AWS Kiro; DL frameworks (PyTorch or TensorFlow); GitHub Copilot.
• GenAI Proficiency: Hands-on with LLMs (GPT-4, Llama), RAG, LangChain, Vector Databases, Knowledge graphs, Agentic AI.
• MLOps and LLM Ops: Docker, Kubernetes, and CI/CD tools for ML.
• AWS Skills: S3, Lambda, Glue, SageMaker, and Bedrock.
• Communication Skills: Excellent verbal and written communication; able to articulate complex concepts clearly.
• Stakeholder Management: Collaborate with business stakeholders and manage expectations.
• Problem-Solving: Independent in fast-paced environments; troubleshoot issues.

Responsibilities

• Architect, fine-tune, and deploy LLMs to improve business applications.
• Build and maintain high-performance ML pipelines and GPU-based inference in cloud environments.
• Collaborate with product managers, data scientists, and engineers to translate requirements into specs.
• Present AI methodologies, performance results, and trade-offs to non-technical stakeholders.
• Stay updated with GenAI advancements and integrate them into production systems.
• Coordinate with offshore teams on project deliverables.

Skills

GenAI Dev

Python

AWS Cloud

MLOps

Communication

Stakeholder Mgmt

Problem Solving

NLP

Education

Engineering degree in CS or equivalent

Tools

Docker

Kubernetes

GitHub Copilot

TensorFlow

PyTorch

Job description

Healthcare,Banking & Finance,Insurance,Telecom,Education,IT/Software

Client:

To Be Discussed Later

Employment Type:

W-2, 1099, C2C

Work Authorization:

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

• 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.