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Machine Learning Engineer
Machine Learning EngineerValence • Toronto, Canada
Machine Learning Engineer

Machine Learning Engineer

Valence • Toronto, Canada
30+ days ago
Job type
  • Full-time
Job description

Valence has built the first-to-market AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance & support to any leader or employee. At Valence, we're not just talking about the future of work – we're actively shaping it.

From your first interaction with us, you'll notice we're different. By working here you won't just implement solutions for our clients; you'll be helping to architect the future of leadership in the age of generative AI. And we'll be honest – this is not for everyone. But for those with an insatiable desire to work fast on complex, unsolved challenges with some of the best talent in tech, this could be the career-defining opportunity you've been waiting for.

The Role

This role is a Machine Learning Engineer role for our conversational AI coaching product designed for Fortune 500 enterprises, reporting into our

Head of AI

  • . In this role you will implement, and optimize machine learning models that power our coaching insights and recommendations. This role is focused on the development and optimization of machine learning models and algorithms, optimizing the underlying ML infrastructure and model development. This role will directly impact our product's core and shape the future of AI-driven leadership coaching for Fortune 500 enterprises.

About Valence

We're a Series A B2B SaaS company, backed by Insight Partners, that's pioneering the first generative AI leadership coach for large enterprises. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together. We've been featured in Harvard Business Review, and our client list reads like a Who's Who of global business, including Coca-Cola, Nestlé, General Mills, ServiceNow, AstraZeneca, Prudential, Citi, CVS and Bristol Myers Squibb.

What You'll Do

You will develop scalable data pipelines, optimize models for performance and accuracy, and evaluate them to ensure they are production-ready.

Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in new ways to advance product goals.

Work with the product team to analyze user behavior and prioritize evolving requirements.

Experiment at a high velocity, conducting statistical analyses, to optimize the end user experience.

Research and development on new Conversational AI approaches leveraging cutting edge LLM / NLP advancements.

Documentation of models, prompts, and processes to increase replicability and drive quality improvements.

Stay current with the latest leading research advancements in ML, LLMs, and Conversational AI.

Support other coding and feature development where required.

What We're Looking For

Bachelor's degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience.

3+ years of professional experience (or equivalent) in software engineering, AI / ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field).

Practical experience and theoretical knowledge of language technologies such as : dialogue / conversational systems, NLP, and Information Retrieval.

Strong foundation in data structures, algorithms, and software engineering principles.

Proficiency in Python and relevant deep learning frameworks; training (e.g. PyTorch, Tensorflow, JAX, Hugging Face Transformers / Adapters), serving (e.g., Hugging Face TGI / / outlines, vLLM).

Experience with LLM model development and deployment ideally including experience with model distillation, supervised fine-tuning using RLHF / DPO, and automatic prompt tuning (e.g. DSPy, TextGrad).

Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and associated ML services.

Strong analytical and problem-solving skills.

Experience structuring and running data-backed experiments.

Strong written and verbal communication skills.

Exposure to early-stage startups, preferably B2B SaaS.

What You'll Get

Ownership of projects and strategic priorities regardless of seniority in our learning-focused environment.

Strong ties to the executive team, a culture of transparency and engagement with strategic decisions.

Options from day one, which means you will be on the ownership track right away.

Competitive salary and equity packages.

Comprehensive health coverage (medical, dental, and vision) from day 1.

Provision of anything you need to be successful - learning tools, hardware, office equipment, software.

401k optionality for US based employees.

Generous PTO, company-wide R&R shutdowns and paid leave for parents.

A WFH stipend, phone stipend and support to work in a We Work or other space as preferred.

Location and Work Environment

If candidates are based in NYC or Toronto they can work hybrid in our offices, otherwise this role can be remote. Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions in the US.

Diversity and Inclusion

We are dedicated to creating a diverse and inclusive environment where everyone feels valued and supported. We encourage applications from candidates of all backgrounds and offer accommodations upon request throughout the hiring process. If you have any questions, please reach out to Allison Langille, Head of People, at jobs@valence.co.

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Machine Learning Engineer • Toronto, Canada

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