ML Engineer With Gen AI

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Job Overview

• Job ID:

J53120

• Job Title:

ML engineer with Gen AI

• Location:

Austin, TX

• Duration:

24 Months + Extension

• Hourly Rate:

Depending on Experience (DOE)

• Work Authorization:

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

H4-EAD, L2-EAD, GC-EAD

• Client:

To Be Discussed Later

• Employment Type:

  W-2, 1099, C2C

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• 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.

• 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.

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

Apply Now

Equal Opportunity Employer

MACHINE LEARNING TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. MACHINE LEARNING TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will MACHINE LEARNING TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract

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