Lead ML Engineer

Valiant Technologies LLC; Atlanta (GA); In loco; USD 150.000 - 230.000; Tempo pieno

Descrizione del lavoro

Valiant Technologies LLC is seeking a highly skilled Machine Learning Engineer to join our AI team in Atlanta. This role bridges cutting-edge research with practical, user-facing applications. You will design, build, and deploy Generative AI models (LLMs, Diffusion) and communicate technical progress to non-technical stakeholders.

A hands-on coder who thrives in collaboration will excel. The ideal candidate will lead GenAI development, production ML pipelines in cloud environments

Competenze

• 10+ years of experience as an ML Engineer, with 1–2 years in Generative AI or NLP projects.
• Strong Python programming and cloud experience (AWS).
• Hands-on with LLMs (GPT-4, Llama), RAG, LangChain, vector databases.
• Familiar with Docker, Kubernetes, and ML CI/CD tooling.
• Excellent communication skills and ability to translate complex AI concepts for non-technical stakeholders.

Mansioni

• Architect, fine-tune, and deploy LLMs and GenAI techniques to improve business applications.
• Build scalable ML pipelines and GPU-based inference systems in cloud environments (AWS/GCP/Azure).
• Collaborate with product managers, data scientists, and engineers to translate requirements into specs.
• Present AI methodologies, performance results, and trade-offs to stakeholders and leadership.
• Stay updated on GenAI advancements and integrate into production systems.
• Coordinate with offshore teams on project deliverables.

Conoscenze

Python

GenAI

LLMs

AWS

MLOps

Communication

Formazione

Engineering degree

Machine learning certification

Strumenti

Docker

Kubernetes

GitHub Copilot

CI/CD

Descrizione del lavoro

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.