Senior Lead Machine Learning Engineer

Harnham; Dallas (TX); Hybrid; USD 150,000 - 180,000; Full time

Job summary

Harnham recrute un Senior Lead Machine Learning Engineer à Dallas pour diriger une équipe spécialisée dans les modèles de langage. Ce rôle combine leadership technique et collaboration multidisciplinaire pour développer des solutions d'IA avancées. Le candidat idéal aura une solide expérience en ML et une formation en informatique, accompagné d'excellentes capacités de communication et de leadership.

Benefits

20% Annual Bonus

Flexible hybrid work setup

Annual learning & development budget

Qualifications

• Minimum 2 ans d'expérience en gestion d'ingénieurs ML.
• Expertise prouvée en LLM et architectures de transformation.
• Compétences solides en Python et bibliothèques ML.

Responsibilities

• Gérer une équipe de 10 ingénieurs en apprentissage automatique.
• Définir la feuille de route pour des solutions basées sur LLM.
• Collaborer avec diverses équipes pour aligner l'exécution technique.

Skills

Leadership

Collaboration

Communication

Production ML

Transformer Models

Education

MSc or PhD in Computer Science

Tools

Python

PyTorch

TensorFlow

MLFlow

Kubernetes

Job description

18 hours ago Be among the first 25 applicants

This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $180,000.00/yr

Direct message the job poster from Harnham

Building AI/ML & Data/Software Engineering Teams Across The US

Senior Lead Machine Learning Engineer – LLM Focus

Salary: $150,000 – $180,000 base + 20% Bonus

Company Overview:

Join a fast-growing, innovative organization at the forefront of artificial intelligence, committed to pushing boundaries in generative AI and Large Language Models (LLMs). We're solving cutting-edge problems with scalable machine learning and deploying solutions across industries, from finance to healthcare to enterprise automation.

Role Overview:

We are seeking a Machine Learning Engineering Manager with deep expertise in LLMs and production-grade ML systems. This is a hands-on leadership role where you'll oversee a team of up to 10 Machine Learning Engineers, while also contributing technically to high-impact AI solutions.

You’ll shape the roadmap for LLM initiatives, drive team performance, ensure technical excellence, and align engineering efforts with business objectives. This role combines engineering leadership, cross-functional collaboration, and strategic execution in a fast-paced environment.

Key Responsibilities:

• Lead and manage a team of up to 10 Machine Learning Engineers, providing mentorship, performance reviews, and career development guidance.
• Define and drive the engineering roadmap for LLM-based solutions and scalable ML systems.
• Collaborate with research, product, and data teams to align technical execution with strategic business needs.
• Guide development of ML/LLM solutions for tasks like summarization, classification, Q&A, and retrieval-augmented generation (RAG).
• Oversee implementation and optimization of transformer models (e.g., GPT, LLaMA, Claude, Mistral).
• Ensure best practices in model training, fine-tuning, evaluation, and deployment.
• Build robust ML pipelines with MLFlow, Airflow, or Kubeflow.
• Manage production deployments using Docker, Kubernetes, and serving frameworks (e.g., TensorFlow Serving, TorchServe, FastAPI).
• Lead efforts in CI/CD, monitoring, versioning, and model drift mitigation.
• Promote a high-performing, collaborative team culture and drive continuous learning and innovation.

Required Qualifications:

• MSc or PhD in Computer Science, Machine Learning, Engineering, or a related STEM discipline.
• 2+ years of experience managing and mentoring ML Engineers or cross-functional ML teams.
• Proven expertise in LLMs and transformer-based architectures (e.g., GPT, BERT, RoBERTa, T5).
• Strong production experience with ML/AI model development, deployment, and lifecycle management.
• Advanced Python skills and familiarity with libraries such as PyTorch, TensorFlow, Hugging Face Transformers.
• Proficiency with cloud platforms (AWS preferred), Kubernetes, and distributed systems (e.g., Spark, Kafka).
• Solid understanding of DevOps practices and CI/CD pipelines for machine learning.
• Exceptional communication and leadership skills; able to bridge technical and business discussions effectively.

Preferred Experience:

• Experience building and scaling retrieval-augmented generation (RAG) pipelines.
• Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and frameworks like LangChain or LlamaIndex.
• Knowledge of RLHF, prompt engineering, and generative model evaluation.
• Experience in regulated or high-security environments is a strong plus.

Compensation and Benefits:

• 20% Annual Bonus
• Flexible hybrid work setup
• Annual learning & development budget, including AI/ML conference attendance

How to Apply:

To express your interest in this opportunity, please submit your CV via the "Apply" link on this page. We look forward to connecting with you!

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst

• Industries

  Research Services and Software Development

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