Sr. Machine Learning Engineer
Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on May 7, 2026. Canoe Intelligence scores B on the Alion truth index.
COMPANY: Canoe Intelligence, A Bloomberg Company
WEBSITE: https://canoeintelligence.com/
TITLE: Sr. Machine Learning Engineer
LOCATION: New York City or London
SALARY = 180,000 - 220,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
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:
For those based in the US, We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
For those in the UK, We offer comprehensive and generous benefits. Primary benefits are healthcare, retirement, life insurance and disability coverage, counselling, paid holidays and paid time off.
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 Intelligence ("Canoe"), a Bloomberg Company, is the data management and intelligence platform powering how the world invests in alts. Our AI-native platform automates the manual data processing, cutting operational costs and risk while future-proofing alts infrastructure for long term growth. Timely, accurate, and comprehensive data arms investment teams to act with the decisiveness of public markets. Canoe’s AI-driven platform was initially incubated in 2013 for Portage Partners LLC, a private multi-family office investment firm, and launched commercially in 2017. In October 2026, Canoe became a part of Bloomberg, combining our private markets data expertise with Bloomberg’s technology, data management capabilities, and global scale. Together, we’re building a connected experience across public and private markets, and investing in the Canoe platform, people, and dedicated client service that got us here. With Canoe, it’s all about making Alts, smarter.
Canoe is an equal opportunity employer and prohibits discrimination in employment. It is Canoe’s policy to provide equal opportunity and access for all persons, and the Company is committed to attracting, retaining, developing, and promoting the most qualified individuals without regard to age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, self-identified or perceived sex, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy, childbirth or related medical conditions, or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law (each, a “Protected Characteristic”).Canoe prohibits treating applicants or employees less favorably in connection with the terms and conditions of employment, in all phases of the employment process, because of one or more Protected Characteristics.