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Anomalo

Senior Machine Learning Engineer - Gen AI and Product Applications

Posted 12 Days Ago
Remote
Senior level
Remote
Senior level
Develop and deploy generative AI products, define quality standards for unstructured data, and collaborate with enterprise clients to implement machine learning solutions.
The summary above was generated by AI

Senior Machine Learning Engineer – Gen AI & Product Applications

We’re looking for a Machine Learning Engineer to help build, deploy and support Anomalo’s suite of Generative AI products that process unstructured data and support enterprise customers. This role is part of a new 0-1 product team, where you'll shape product quality and integrate multiple LLMs into real-world applications.

What You’ll Do

  • Develop and deploy GenAI-driven products, including customer-facing applications and internal tools for engineering teams.
  • Work with unstructured data and define product quality standards for a rapidly evolving space.
  • Collaborate with design partners and enterprise customers to understand how ML and LLMs can be applied effectively.
  • Build and refine retrieval-augmented generation (RAG) models and fine-tune LLMs for specific use cases.
  • Own projects from concept to production, ensuring scalability and performance in real-world environments.

What We’re Looking For

  • Strong Python expertise (ML engineering, data processing, and API development).
  • Experience deploying GenAI/LLM-based applications (e.g., chatbots, recommendation systems).
  • Familiarity with OpenAI, Anthropic Claude, and similar GenAI platforms.
  • Background in production-scale ML applications, particularly LLMs for enterprise use cases.
  • Self-starter mentality—comfortable with ambiguity and taking initiative in a fast-moving environment.

Nice to Have

  • Experience with RAG, fine-tuning LLMs, or scaling GenAI models.
  • Background in data-driven product development or ML for incident response/support systems.

Why Join Us?

  • Work on cutting-edge GenAI and LLM applications with real impact.
  • Exposure to a variety of enterprise customers and ML use cases.
  • Collaborative, high-growth environment where your work directly shapes the product.

This is a unique opportunity for an ML engineer who thrives in building and launching real-world AI products. If you're excited about applying LLMs to practical use cases, we’d love to hear from you!
The estimated salary range for this role is between $210,000 - $265,000 plus meaningful equity.   

Please note, we can only consider candidates who reside and are authorized to work in the continental United States. 

Perks of working at Anomalo:
  • 🎯 Make An Impact: Join a growing company that delights our customers. Our modern UI and rich visualizations help our customers solve unknowns and anticipate data issues before they happen.
  • 🔍 A values-driven, open and transparent culture that supports autonomy and growth.
  • 🏡 Fully Remote: We were fully remote before it was a thing, and we believe your best work happens on your schedule. We offer a generous $1,000 stipend to ensure your remote office is comfortable.
  • ✈ Quarterly Onsites: While we love the flexibility of being remote-first, we also recognize the value of spending time together in person. We make time to get together (in a new destination!) for a company-wide offsite each quarter.
  • 🌴 Generous Time Off: Enjoy 17 company holidays and unlimited vacation time that we encourage you to take. We also have a company-wide winter break the last week of the year.
  • 🩹 Health Benefits: Comprehensive family-friendly medical, dental, and vision insurance plans. Anomalo covers 90% of your premiums. We provide access to family planning and reproductive care for our employees and their families by partnering with Carrot Fertility. We provide mental health and wellness benefits for all employees, covered at 100%.
  • 🍼 Family Comes First: We offer 16 weeks of parental leave, during which you will receive your full pay.
  • 💸 Investment in the company & your future: Every employee is granted a meaningful equity package. We also offer life insurance and a 401(k) plan.

Many of our benefits and perks are designed for full-time employees, with some available only to team members based in the United States.

What we value:

  • Own It: We don’t just do our jobs—we own getting to the best results across the company.
  • Act & Adapt: We prioritize action, learn from mistakes, and continuously improve with humility and curiosity.
  • Thrive Together: We embrace diversity, assume best intentions, and support each other to succeed as a team.
  • Opacity Zero: Thoughtful transparency enables us to work autonomously and make great decisions.
  • Customer Focus: We anticipate, innovate for, and deliver what matters most to our current and future customers.
  • Work Smart: Work when, where, and how you’re most effective—outcomes matter more than hours.
About Anomalo

Anomalo is the automated AI solution that integrates with the modern data stack to monitor data quality. Using unsupervised learning, it detects complex issues like distribution changes that static rules miss. With built-in root cause analysis, Anomalo identifies anomalies, their causes, and their impact, helping data teams focus on building instead of debugging.

We’re rapidly growing and work with some of the biggest brands leveraging data today, like Block, Discover, Atlassian, and Included Health. Backed by $82M in seed through Series B extension funding from top-tier firms, including SignalFire, Norwest Venture Partners, Databricks Ventures, Foundation Capital, Two Sigma Ventures, and First Round Capital, Anomalo is enabling companies to make better data-driven decisions.


We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the  interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for confidential accommodation requests will be shared.

 

Anomalo Applicant Privacy Policy

Top Skills

Genai
Llms
Python
Retrieval-Augmented Generation

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