T
AI

Machine Learning Engineer

TalentDome Staffing ·

Actively hiring Posted 7 months ago

TalentDome Staffing is partnering with a rapidly growing, Florida-based AI startup that is set to revolutionize compliance workflows in the financial services industry.

Our client is building a neutral compliance layer to manage complex, document-heavy processes at scale. They are a pre-Series A company with a small, highly technical team of 17 (including 3 in the US). They are looking for a hands-on, mid-level Machine Learning Engineer to join their core team, report to the Lead Solutions Architect, and work alongside the Senior Data Scientist (Scott).

This is a
100% "hands-on-keyboard" role
. We are looking for a "doer" who is passionate about building, training, and deploying models from the ground up.

What You’ll Do

As a core Machine Learning Engineer, you will be responsible for the entire model lifecycle. You won't just be running analytics; you'll be building the engine.

  • Design, build, train, and deploy machine learning models using PyTorch (preferred) and TensorFlow.
  • Own the end-to-end model development process: from data gathering and feature engineering (handling outliers, normalization) to training and implementation.
  • Perform rigorous model evaluation and validation, and be able to clearly explain your choice of metrics (e.g., F1-score, ROC/AUC, Accuracy vs. Precision ).
  • Work with a variety of model architectures (Transformers, CNNs, RNNs, XGBoost, etc.) to find the best solution for the problem.
  • Collaborate closely with the senior data science and architecture team to rapidly prototype, iterate, and ship models to production.

What You'll Bring (The "Must-Haves")

We are looking for a mid-level engineer with a "startup attitude." The right mindset is more important than years of experience.

  • Experience: 3-5 years of hands-on experience as a Machine Learning Engineer.
  • Core Skill: A strong, practical understanding of PyTorch (highly preferred) and/or TensorFlow.
  • ML Fundamentals: Deep, practical knowledge of ML fundamentals. You must be able to confidently explain the difference between accuracy and precision, what an F1-score is, and how to read a ROC curve.
  • Proven "Builder": You must have experience building and training models "from the ground up," not just running analytics in a notebook or using pre-built APIs.
  • Feature Engineering: Strong skills in feature engineering, including handling outliers, normalization, and cleaning skewed data.
  • Startup Attitude (Essential): You are a "doer" who is passionate, driven, and independent. You thrive in a fast-paced environment, are willing to wear multiple hats, and have an "ask for forgiveness, not permission" mentality.

What We Offer

  • A competitive base salary of up to $180,000 USD .
  • Meaningful equity in a high-growth company.
  • A comprehensive benefits package.
  • A 100% fully remote work environment.

Please note:
We are not able to provide visa sponsorship for this position at this time.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Remote Ai Machine Learning Data Science Pytorch Tensorflow
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.