Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Sr. Machine Learning Engineer

Canoe Intelligence
City of London
1 week ago
Create job alert

COMPANY: Canoe Intelligence

WEBSITE: https://canoeintelligence.com/

TITLE: Sr. Machine Learning Engineer

LOCATION: New York City or London (hybrid) / Fully Remote in the United States or United Kingdom

SALARY: $180,000 - $220,000 (based on NYC, will be adjusted for geo)

The Role

We are looking for a Senior Machine Learning Engineer to design and deploy models that make sense of highly complex, unstructured financial documents, enabling us to deliver data with unprecedented accuracy, speed, and trust. You’ll work hands-on with LLM and other ML Models, helping scale Canoe’s platform while shaping how alternative investment firms interact with their data.

What You’ll Do
  • Design, train, and evaluate ML models for document classification, entity extraction, summarization, and information retrieval.
  • Fine-tune and optimize large language models for domain specific use cases, optimizing their performance for accuracy, efficiency, and scalability.
  • Work closely with data engineering teams to preprocess and engineer features from large datasets to enhance the performance of machine learning models.
  • Build scalable, production-ready ML services with strong observability, monitoring, and retraining capabilities.
  • Contribute to Canoe’s MLOps stack, including CI/CD for models, feature stores, evaluation frameworks, and data versioning.
  • Collaborate with product managers, software engineers, and other stakeholders to integrate machine learning models into end-to-end solutions.
  • Stay current with advancements in LLMs, Agentic AI, and ML, and translate new research into practical improvements to Canoe’s technology stack.
  • Conduct code reviews to ensure code quality and provide mentorship to junior members of the machine learning team.
What We’re Looking For
  • Minimum of 5 years of experience in applied ML engineering, with a focus on NLP, information extraction, or LLMs.
  • Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch).
  • Strong understanding of MLOps (Docker, Kubernetes, CI/CD for ML, experiment tracking).
  • Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude Code agent) to accelerate software development, prototyping, testing, and deployment of ML solutions.
  • Problem-solver with a product mindset and bias toward outcomes.
  • Excellent communication skills; able to partner across engineering, product, and business teams.
  • Comfortable in fast-paced, agile startup environments.
  • Bachelor’s degree in computer science or related field.

Preferred

  • Master Degree or PhD in computer science or related field
  • Experience in training and deploying large language models.
  • Familiarity with cloud computing platforms and distributed computing.
  • Familiarity with modern ML Ops tools such as Modal, Weights and Biases, Sagemaker, etc.
  • Experience with LLM fine-tuning techniques such as LoRA, QLoRA, or parameter-efficient training frameworks (e.g., Unsloth).
What You’ll Get
  • Medical, dental, vision benefits
  • Flexible PTO
  • 401(k)
  • Flexible work from home policy
  • Home office stipend
  • Employee Assistance Program
  • Gym/Wifi reimbursement
  • Education assistance
  • Parental Leave
Our Values
  • Client First —> Listen, and deliver client-centric solutions
  • Be An Owner —> Take initiative, improve situations, drive positive outcomes
  • Excellence —> Always set the highest standard for yourself and others
  • Win Together —> 1 + 1 = 3
Who We Are

Canoe is reimagining alternative investment data processes for hundreds of leading institutional investors, capital allocators, asset servicing firms and wealth managers. By combining industry expertise with the most sophisticated data capture technologies, Canoe’s technology automates the highly-frustrating, time-consuming, and costly manual workflows related to alternative investment document and data management, extraction and delivery. With Canoe, clients can refocus capital and human resources on business performance and growth, increase efficiency, and gain deeper access to their data. Canoe’s AI-driven platform was developed in 2013 for Portage Partners LLC, a private investment firm.

Canoe is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer, AI Foundations

Machine Learning Engineer, AI Foundations

Data Scientist | Python | SQL | Statistics | Machine Learning | Hybrid, Oxford

Sr. Data Scientist, GenAI Algorithms (Based in Dubai)

Associate Director, AI Data Scientist

Solution Consultant - IT & Data Science

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.

Why the UK Could Be the World’s Next AI Jobs Hub

Artificial Intelligence (AI) has rapidly moved from research labs into boardrooms, classrooms, hospitals, and homes. It is already reshaping economies and transforming industries at a scale comparable to the industrial revolution or the rise of the internet. Around the world, countries are competing fiercely to lead in AI innovation and reap its economic, social, and strategic benefits. The United Kingdom is uniquely positioned in this race. With a rich heritage in computing, world-class universities, forward-thinking government policy, and a growing ecosystem of startups and enterprises, the UK has many of the elements needed to become the world’s next AI hub. Yet competition is intense, particularly from the United States and China. Success will depend on how effectively the UK can scale its strengths, close its gaps, and seize opportunities in the years ahead. This article explores why the UK could be the world’s next global hub for artificial intelligence, what challenges it must overcome, and what this means for businesses, researchers, and job seekers.