This is a Fully Remote Job
1. About Our Client:
The organization operates in the financial technology sector, focusing on replacing outdated financial processes with innovative automation tools. It supports a broad range of businesses, from startups to established brands, by providing solutions that enable smarter decision-making and operational control. The company processes millions of financial documents monthly, leveraging machine learning to convert unstructured data into actionable financial insights. It maintains a remote-first work environment with physical offices in San Jose, California, and Draper, Utah, fostering collaboration to deliver impactful solutions.
2. About the Opportunity:
The Staff Machine Learning Engineer role is a senior individual contributor position responsible for advancing the technical direction of machine learning initiatives within the AI Product Engineering team. The role involves architecting and building next-generation machine learning systems, including LLM-based extraction, fine-tuned open-weight models, intelligent routing, and foundational data infrastructure. This position significantly influences the evaluation, deployment, and iteration of production models while mentoring engineers to elevate the organization''s ML capabilities.
3. Responsibilities:
- Lead technical direction for end-to-end ML initiatives across document understanding, field extraction, and model-serving infrastructure.
- Develop and deploy models, maintaining hands-on involvement in prototyping and production coding.
- Oversee the LLM strategy, including fine-tuning foundation models and making informed build-versus-buy decisions.
- Apply research insights to production challenges through rigorous experimentation and adaptation.
- Design data pipelines for continuous model improvement, incorporating labeling, feedback, and monitoring.
- Establish standards for model evaluation, calibration, reproducibility, and responsible deployment.
- Mentor mid-level and senior ML engineers through code reviews, pairing, and technical guidance.
4. Requirements:
- Minimum 8 years of relevant experience with a Bachelor''s degree, or 6 years with a Master''s degree, or 3 years with a PhD, or equivalent.
- At least 8 years in software/ML engineering at a Staff level or equivalent, with hands-on expertise in modern ML/AI tools such as PyTorch and distributed training.
- Experience fine-tuning LLMs, including supervised fine-tuning, LoRA/QLoRA, preference optimization, and production-scale deployment.
- Deep understanding of open-weight and foundation models, including document AI and layout-aware models.
- Production experience in recommendation systems, personalization, or search/ranking, with handling of user behavior data and feedback loops.
- Strong data reasoning skills covering sampling, evaluation design, confidence calibration, and distribution shift analysis.
- Research-oriented with a demonstrated ability to translate literature into impactful production results.
5. Pay Range and Compensation Package:
- The pay range and compensation package for this role will be determined based on the candidate’s experience, skills, and other relevant factors.
Equal Opportunity Statement:
Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.
Note:
TalentHop is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.