Senior Lead Machine Learning Engineer - LLM Focus

Harnham; Ontario; On-site; CAD 150,000 - 180,000; Full time

Job summary

Join Harnham as a Senior Lead Machine Learning Engineer focusing on LLMs. This hands-on leadership role involves overseeing a team of ML engineers and shaping the engineering roadmap for innovative AI solutions. Work in a fast-paced environment at the cutting edge of AI technology, contributing to impactful projects across various industries.

Benefits

20% Annual Bonus

Flexible hybrid work setup

Annual learning & development budget

Comprehensive benefits package (health, dental, vision)

Qualifications

• 2+ years of experience managing and mentoring ML engineers.
• Strong production experience with ML model development.
• Proven expertise in LLMs and transformer-based architectures.

Responsibilities

• Lead a team of up to 10 Machine Learning Engineers.
• Define the engineering roadmap for LLM-based solutions.
• Guide the development of ML solutions for tasks like summarization and classification.

Skills

Leadership

Machine Learning

Deep Learning

Collaboration

Communication

Education

MSc or PhD in Computer Science or related STEM discipline

Tools

Kubernetes

TensorFlow

PyTorch

MLFlow

Airflow

Job description

Senior Lead Machine Learning Engineer - LLM Focus

Senior Lead Machine Learning Engineer - LLM Focus

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

Location: Toronto

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!

Senior Lead Machine Learning Engineer - LLM Focus

Location: Toronto

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:

• Base Salary: $150,000 - $180,000
• 20% Annual Bonus
• Flexible hybrid work setup
• Comprehensive benefits package (health, dental, vision)
• 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!

Desired Skills and Experience

LLM, MLOps

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Analyst

• Industries

  Media and Telecommunications

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