Early Career Machine Learning Engineer

EvenUp; Toronto; Hybrid; CAD 65,000 - 90,000; Full time

Job summary

EvenUp is seeking an Early Career Machine Learning Engineer to support our AI R&D team focused on enhancing justice through technology. In this role, you will develop and deploy machine learning models for our claims-intelligence platform, working closely with experienced professionals to shape impactful solutions. The position offers an excellent opportunity to grow your expertise in AI and data science within a dynamic startup environment while contributing to meaningful work.

Benefits

Medical, dental, and vision insurance plans

Flexible paid time off

Home office stipend

Paid parental leave

Qualifications

• Hands-on experience with NLP or generative-AI techniques.
• Solid grounding in machine-learning fundamentals.
• Eagerness to learn and iterate quickly.

Responsibilities

• Explore, implement, and benchmark ML/NLP/generative-AI methods.
• Clean, annotate, and transform case data.
• Design experiments and analyze results.

Skills

Machine Learning Fundamentals

Natural Language Processing

Analytical Thinking

Education

Ph.D. or M.S. in Computer Science, Machine Learning, Data Science, Statistics, or Computational Linguistics

Tools

Python

PyTorch

TensorFlow

spaCy

Job description

Join to apply for the Early Career Machine Learning Engineer role at EvenUp

Join to apply for the Early Career Machine Learning Engineer role at EvenUp

EvenUp is one of the fastest-growing generative AI startups in history, on a mission to level the playing field for personal injury victims, which range from motor vehicle accidents to child abuse cases. Our products empower law firms to secure faster settlements, higher payouts, and better outcomes for those who need it most.

We are looking for a curious, impact-driven early career Data Scientist / Machine Learning Engineer to join our AI R&D team. You’ll develop and deploy models that power Piai, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI. Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you’ll turn raw legal and medical data into production-ready models that directly improve justice for personal-injury clients.

What you’ll do:

• Model research & prototyping – Explore, implement, and benchmark ML/NLP/generative-AI methods (e.g., LLM fine-tuning, retrieval-augmented generation, document understanding).
• Data preparation & feature engineering – Clean, annotate, and transform structured and unstructured case data; build reusable datasets and data loaders.
• Experimentation workflow – Design experiments, run A/B tests, analyze results, and communicate findings to the wider product and engineering teams.
• Productionization – Help integrate models into our microservices architecture; collaborate with MLOps engineers on packaging, testing, monitoring, and scaling.
• Cross-functional collaboration – Pair with product managers, legal analysts, and software engineers to translate pain points into ML solutions and measurable product improvements.
• Continuous learning – Stay current with research in LLMs, representation learning, and prompt engineering; share insights through internal talks and docs.
  
  

What we look for:

• Education: Ph.D. or M.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a closely related field
• Core expertise:
• Solid grounding in machine-learning fundamentals (supervised & unsupervised learning, evaluation metrics, overfitting/regularization).
• Hands-on experience with NLP or generative-AI techniques (e.g., transformers, embeddings, sequence-to-sequence models, LLMs).
• Technical stack:
• Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, spaCy, or similar.
• Familiarity with SQL and basic data-engineering concepts (ETL, versioned datasets, notebooks).
• Nice-to-have: exposure to cloud platforms (AWS/GCP), experiment-tracking tools (Weights & Biases, MLflow), or containerized deployment (Docker/Kubernetes).
• Mindset & people skills:
• Eagerness to learn from senior teammates and iterate quickly in a fast-moving startup.
• Clear, concise communication—both written and verbal.
• Strong analytical thinking and a bias toward shipping pragmatic, high-impact solutions.
  

Location: Hybrid – We have offices in San Francisco and Toronto

Notice to Candidates:

EvenUp has been made aware of fraudulent job postings and unaffiliated third parties posing as our recruiting team – please know that we have no affiliation or connection to these situations. We only post open roles on our career page (https://jobs.ashbyhq.com/evenup) or reputable job boards like our official LinkedIn or Indeed pages, and all official EvenUp recruitment emails will come from the domains @evenuplaw.com, @evenup.ai, @ext-evenuplaw.com or [e-mail] email address.

If you receive communication from someone you believe is impersonating EvenUp, please report it to us by emailing [e-mail]. Examples of fraudulent email domains include “careers-evenuplaw.com” and “careers-evenuplaws.com”.

Benefits & Perks:

Our goal is to empower every team member to contribute to our mission of fostering a more just world, regardless of their role, location, or level of experience. To that end, here is a preview of what we offer:

• Choice of medical, dental, and vision insurance plans for you and your family
• Flexible paid time off
• 10 US observed holidays, and Canadian statutory holidays by province
• A home office stipend
• 401(k) for US-based employees
• Paid parental leave
• Sabbatical program
• A meet-up program to get together in person with colleagues in your area
• Offices in San Francisco, Los Angeles, and Toronto
  
  

Please note the above benefits & perks are for full-time employees

About EvenUp:

EvenUp is on a mission to level the playing field in personal injury cases. EvenUp applies machine learning and its AI model known as Piai to reduce manual effort and maximize case outcomes across the personal injury value chain. Combining in-house human legal expertise with proprietary AI and software to analyze records. The Claims Intelligence Platform provides rich business insights, AI workflow automation, and best-in-class document creation for injury law firms. EvenUp is the trusted partner of personal injury law firms. Backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures (BCV), SignalFire, NFX, DCM, and more, EvenUp’s customers range from top trial attorneys to America’s largest personal injury firms. EvenUp was founded in late 2019 and is headquartered in San Francisco. Learn more at www.evenuplaw.com.

EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Seniority level

• Seniority level

  Internship

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Technology, Information and Internet

Referrals increase your chances of interviewing at EvenUp by 2x

Sign in to set job alerts for “Machine Learning Engineer” roles.

Software Engineer, Backend (All Levels / All Teams)

Software Engineer I, Entry Level (Fall 2024-Spring 2025) - Toronto

Graduate 2025 Software Engineer I, Canada

Software Developer Full Stack (Junior) 9063-1115

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.