Early Career Machine Learning Engineer

Jobright.ai; San Francisco (CA); On-site; USD 130,000 - 230,000; Full time

Benefits offered by this job

Medical insurance

Vision insurance

401(k)

Job summary

A leading AI startup seeks a Machine Learning Engineer to develop and deploy models, collaborating with teams to enhance justice outcomes for clients. Ideal candidates will excel in machine learning, NLP, and generative AI, ensuring impactful solutions tailored to client needs.

Qualifications

• Ph.D. or M.S. in a relevant field required.
• Hands-on experience with NLP or generative AI techniques essential.
• Proficiency in Python and ML/NLP libraries necessary.

Responsibilities

• Model research & prototyping using ML/NLP methods.
• Data preparation & feature engineering for case data.
• Design experiments and analyze results.

Skills

Machine Learning

Natural Language Processing

Generative AI

Python

Data Science

Analytical Thinking

Clear Communication

Education

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

Tools

PyTorch

TensorFlow

SQL

Job description

21 hours ago Be among the first 25 applicants

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EvenUp is one of the fastest-growing generative AI startups in history, on a mission to level the playing field for personal injury victims. The role involves developing and deploying models for Piai, focusing on machine learning, natural language processing, and generative AI, while collaborating with a diverse team to improve justice outcomes for clients.

Responsibilities

• 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.

Qualification

Required

• Ph.D. or M.S. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a closely related field
• 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)
• 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)
• 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

Preferred

• exposure to cloud platforms (AWS/GCP)
• experiment-tracking tools (Weights & Biases, MLflow)

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Software Development

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Inferred from the description for this job

Medical insurance

Vision insurance

401(k)

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