Janea Systems - Lead Machine Learning Engineer
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Requirements
• 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.
Benefits
• 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.
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