Machine Learning Manager, Cohere
Applied Machine Learning, UK/EU
Natural language processing AI platform
Be an early applicant
Natural language processing AI platform
501-1000 employees
Be an early applicant
501-1000 employees
Company mission
To build machines that understand the world, and to make them safely accessible to all.
Role
Who you are
- The ideal candidate brings deep expertise in AI/ML, a strong track record of building and mentoring high-performing teams, and the ability to turn complex technical capabilities into real business outcomes
- Bachelor’s degree in Computer Science, Machine Learning, or a related field (Master’s or PhD preferred)
- 8+ years in AI/ML, including several years in technical leadership roles
- Proven success leading large ML teams and delivering complex AI solutions at scale
- Experience with enterprise deployments, including custom model development and fine-tuning
- Deep understanding of LLMs, their training, deployment, and real-world constraints
- Hands-on experience with RAG pipelines, agentic systems, and multi-modal applications
- Proficiency in ML frameworks such as PyTorch or TensorFlow
- Familiarity with modern cloud platforms (AWS, GCP, Azure) and ML infrastructure best practices
- Strong ability to translate business requirements into scalable ML solutions
- Track record of product thinking and technical decision-making aligned with customer needs
- Exceptional communicator, capable of aligning technical execution with business goals
- Experienced mentor who inspires excellence, collaboration, and growth in technical teams
What the job involves
- We are looking for a Machine Learning Manager to help lead our Applied ML team in building and delivering cutting-edge AI solutions tailored for enterprise customers. This is a high-impact leadership role that combines strategic direction, technical oversight, and customer collaboration
- You’ll manage a world-class team of ML engineers focused on building scalable, production-grade systems—working across modalities and domains such as reasoning, code, RAG, tools, and agents
- Define and drive the long-term vision for the Applied ML team in alignment with Cohere’s product and business goals
- Shape the roadmap for custom model development, fine-tuning, and advanced implementations that address nuanced enterprise challenges
- Collaborate closely with executive leadership to prioritize high-impact initiatives and strategic customer engagements
- Lead and grow a high-performing team of ML engineers through hiring, coaching, and mentorship
- Foster a culture of ownership, innovation, and continuous learning
- Establish and evolve team processes to maximize productivity and execution speed
- Partner with Product to define and deliver novel, scalable ML solutions that differentiate Cohere in the market
- Guide the development of reusable frameworks and abstractions that streamline deployment across customer use cases
- Oversee performance optimization and evaluation of models in real-world enterprise environments
- Act as a trusted technical advisor to strategic customers—translating needs into actionable plans
- Lead delivery efforts from prototyping through to production deployment on customer infrastructure
Our take
The AI industry biggest stakeholders insist that the next step in enhancing web experiences will be through natural language interactions. While this may be true, only companies with considerable resources can reasonably address the gap needed to bring NLP to the forefront of web integration. Cohere was founded to address this shortfall between NLP development, widespread usage, and the resources required.
Cohere works on building top-of-the-class NLP processing models and software which it makes available to customers through APIs and custom solutions. In a strategic move, the company has partnered with Google Cloud, giving them access to resources that will undoubtedly push the field of NLP forward. This allows Cohere to serve as middlemen by offering a wide range of customers a product built on unmatched technology.
AI is currently a worldwide talking point and so it is no surprise that Cohere has seen rapid development, and raised $270M in a 2023 funding round. The company plans to introduce a dialogue model that would resemble ChatGPT, however, in this case, its technology would be mainly accessible to developers and businesses.
Steph
Company Specialist at Welcome to the Jungle
Insights
192% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Aug 2025
$500m
LATE VC
Jul 2024
$500m
SERIES D
Total funding: $1.4bn
Company benefits
- We cover 100% of premiums across health, dental, vision & travel
- We offer RRSP, 401K, and Pension Scheme contributions
- We offer lunch and fitness studio credits and a quality time fund which can be spent on things like dog walking and laundry services
- We want everyone who contributes to our success to get a ‘piece of the pie’
- Work Remote & PTO
- We know that some people work better at home, so we are remote-first, and sure that all meetings, events, and opportunities are set up for our distributed team
- Every employee at Cohere gets 6 weeks of paid time off & US and Canadian federal holidays, and we provide unlimited sick days
- All new parents (including those who adopt or go through a surrogate journey) are eligible to receive 100% salary for 6 months in Canada, the US, and the UK
- The decision and journey to having kids is different for each person and family. Part of our commitment to diversity is being able to support the widest variety of these scenarios as we can so we offer financial support for egg freezing and IVF for those in the US, Canada and the UK
- Every employee at Cohere receives an annual $2,000 education fund to use as they please
Company HQ
Grange Park, Toronto, ON
Leadership
Aidan Gomez
(CEO)Has a PhD in Computer Science from Oxford University. Previously worked as a Researcher at Google (Brain) and FOR.ai
Ivan Zhang
(CTO)Previous experience working in research and engineering at For.ai, Cortex labs, Pressly and Ranomics.
Nick Frosst
(CTO)Previously worked as a Research Engineer at Google (Brain).
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