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Lead Machine Learning Engineer

Roles & Responsibilities

  • 8+ years of experience in software engineering, machine learning engineering, or applied AI.
  • 3+ years of experience in technical leadership or mentoring engineering teams.
  • Strong experience developing and deploying machine learning models in production environments.
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or similar.

Requirements:

  • Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients.
  • Work at the intersection of machine learning, distributed systems, and production software engineering to transform cutting-edge ML research into robust, production-grade solutions.
  • Guide ML architecture decisions and mentor engineers.
  • Collaborate with cross-functional teams to deliver high-impact AI solutions across multiple industries.

Job description

Janea Systems (USA) is a dynamic team of the best & brightest software engineering specialists and solutions innovators, from around the world. From kernel to cloud, we provide high-impact software development services to Fortune 500 companies.

We are seeking an exceptionally talented Lead Machine Learning Engineer to join our rapidly growing consulting team. In this role, you will lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients.
You will work at the intersection of machine learning, distributed systems, and production software engineering, helping transform cutting-edge ML research into robust, production-grade solutions. As a Lead ML Engineer, you will guide ML architecture decisions, mentor engineers, and collaborate with cross-functional teams to deliver high-impact AI solutions across multiple industries.

  

Location

Fully Remote/ European Residence required

Compensation

Salary

Work Schedule

Full time/ Flexible working hours

Reports to

Head of Engineering

Member of

Engineering Team

 

To be considered for this position, you must have the following qualifications: 

  • 8+ years of experience in software engineering, machine learning engineering, or applied AI.
  • 3+ years of experience in technical leadership or mentoring engineering teams.
  • Strong experience developing and deploying machine learning models in production environments.
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or similar.
  • Experience designing scalable ML systems and data pipelines.
  • Strong programming skills in Python and experience with backend or distributed systems.
  • Experience with cloud platforms (AWS, Azure, or GCP).
  • Experience with containerization and deployment technologies (Docker, Kubernetes).
  • Strong understanding of MLOps practices and model lifecycle management.
  • Excellent problem-solving skills and ability to work independently in remote environments.
  • Strong written and spoken English communication skills.
  • Degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

 

Ideal candidates will also have: 

  • Experience working with LLMs, generative AI systems, or deep learning architectures.
  • Experience building ML platforms or internal AI tooling.
  • Familiarity with distributed training and large-scale data processing frameworks.
  • Experience with feature stores, model monitoring, and ML observability tools.
  • Experience delivering ML solutions in client-facing consulting environments.

 

Why join Janea? Because world-class talent deserves world-class opportunities. What we offer: 

  • Competitive compensation with benefits, paid vacation, and sick leave.
  • The opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges. 
  • Ultra-flexible working conditions – we provide a generous office equipment allowance so you can work from home, we can also provide you with a desk at an office/coworking facility near you, or use both. No business travel necessary. 
  • An enjoyable, start-up work environment, with excellent opportunities for professional growth and development.
  • Flexible working hours – as a remote-first company, our focus has always been on getting the job done well, not when or where it gets done. 

 

#LI-DNI

 

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