Verified Job
Work from home
Machine Learning Engineer with Gen AI/Atlanta, GA/Only Locals
Work from home
#670632
Remote / WFH
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, ETS LLC, is seeking the following. Apply via Dice today!
Machine Learning Engineer with Gen AI
Years Of Experience 10 to 15 Years Atlanta, GA
Only Locals 3 Days Hybrid
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.
Roles & Responsibilities 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/Google Cloud Platform/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: Excellent verbal 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
Machine Learning Engineer with Gen AI
Years Of Experience 10 to 15 Years Atlanta, GA
Only Locals 3 Days Hybrid
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.
Roles & Responsibilities 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/Google Cloud Platform/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: Excellent verbal 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
