Senior Machine Learning Engineer

edenity have partnered up with a SaaS company at the forefront of legal tech seeking a Senior Machine Learning Engineer to help shape the next generation of their AI capabilities.

Having outgrown their early product scope, the company is now zeroing in on AI-first workflows designed for professional users operating in complex, high-stakes environments. Their next product evolution focuses on embedding advanced natural language processing and large language model (LLM) technologies into their platform - empowering more intelligent, intuitive, and scalable decision-making.

This is a rare opportunity to work on real-world, applied LLM challenges where innovation is essential, but rigour and responsibility are non-negotiable. The domain is serious. The impact is tangible. The technical bar is high.

What You’ll Be Doing

• Designing, building, and deploying production-ready ML solutions particularly those leveraging LLMs for document understanding and user engagement.
• Collaborating cross-functionally with product, design, and engineering teams to integrate models in a way that is robust, explainable, and truly useful.
• Experimenting with methods such as retrieval-augmented generation (RAG), few-shot prompting, and domain-specific model fine-tuning.
• Iterating quickly while upholding high standards of reliability, quality, and trust in a regulated, high-precision domain.
• Staying close to the evolving landscape of foundation models and actively proposing novel approaches to elevate the product.

Ideal Experience

• A strong background in machine learning or NLP, ideally with hands-on experience working with LLMs or document-centric AI systems.
• A track record of taking ML solutions from prototype to production—especially in product-led environments.
• Fluency in modern ML tools and frameworks (e.g., PyTorch, HuggingFace Transformers, Vector Databases), along with a working knowledge of ML ops best practices.
• Excellent communication skills—comfortable navigating both technical complexity and product-level nuance.
• Experience working with unstructured, domain-sensitive data (e.g., contracts, legal, financial, or technical documents) is a major plus.
• Familiarity with workflow-based or collaborative platforms is beneficial, but not essential.

Why This Role Stands Out

• A genuine opportunity to work on applied LLM problems with real-world constraints and real-world users.
• A mission-led team that prizes trust, transparency, and factual precision—where AI is held to a higher standard.
• A product-centric culture where ML is not an afterthought, but a core pillar of the strategy.
• Access to senior technical leadership and advisors who understand how to build and scale responsible AI systems.

The Process

The hiring process is designed to ensure technical depth, cultural alignment, and mutual clarity while accommodating the realities of a busy market:

1. Introductory conversation with the product & engineering leadership team
2. Deep technical dive with the engineering lead
3. Case study with core-team + founder(s)

This is a long-term, high-impact hire for someone who wants to grow with a team and product that values depth, integrity, and lasting outcomes.