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Staff Machine Learning Research Scientist

16 hours, 44 minutes ago
United States
Full-time
Lead
AI Research Scientist
Data Science and Analytics
Apache Airflow AWS GitHub Kubernetes Machine Learning MLOps Python PyTorch Snowflake Transformers
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SmarterDx

SmarterDx

SmarterDx ensures revenue integrity by leveraging A.I. algorithms to uncover missed opportunities in clinical data, optimizing tasks for accurate ICD 10 coding and guaranteeing a 5:1 ROI.

Professional Services
11-50
Founded 2019
View All Jobs 19

Description

  • Lead end-to-end machine learning research from idea generation through production deployment and monitoring.
  • Design, implement, and evaluate novel methods for LLM alignment using proprietary clinical data.
  • Develop and evaluate approaches for hallucination detection, attribution, and model reliability.
  • Build and curate high-quality datasets with strong evaluation design and benchmark integrity.
  • Critically assess academic literature and translate the strongest ideas into practice.
  • Establish best practices for experimental design, statistically sound evaluation, and reproducibility.
  • Collaborate with engineering teams to productionize models across MLOps, infrastructure, and deployment.
  • Develop methods for long-context and multimodal modeling across structured and unstructured clinical data.
  • Mentor other researchers and help raise research quality standards across the team.
  • Contribute externally through papers, talks, and recruiting.

Requirements

  • Strong track record of ML research, ideally with publications in top-tier venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or AAAI.
  • Proven ability to distinguish high-quality from low-quality research, especially in fast-moving areas like LLMs.
  • Deep understanding of LLM failure modes, especially hallucinations, and how to evaluate and mitigate them.
  • Experience designing rigorous evaluation frameworks and building high-quality test datasets.
  • Strong intuition for dataset quality, bias, and benchmark design with a data-centric AI mindset.
  • Hands-on experience training large-scale deep learning models in multi-GPU or distributed systems.
  • Deep understanding of modern neural architectures such as transformers, SSMs, and encoder/decoder models.
  • Strong programming skills in Python and ML frameworks such as PyTorch or JAX.
  • Experience deploying ML models into production systems and monitoring their performance.
  • Clear and proactive communication skills, with the ability to explain complex ideas and critique work effectively.
  • Experience with inference optimization techniques such as vLLM, KV caching, or speculative decoding, preferred.
  • Familiarity with MLSys concepts such as parallelism strategies and distributed training infrastructure, preferred.
  • Experience working with clinical or healthcare data, preferred.
  • Background in retrieval systems, graph-based learning, or multimodal modeling, preferred.

Benefits

  • Base salary of $220k-$260k.
  • Comprehensive medical, dental, and vision coverage with 75% of premiums covered depending on the plan.
  • Paid parental leave of up to 12 weeks for birth or adoption.
  • Remote-first work environment with the ability to work from anywhere in the U.S.
  • Unlimited PTO plus 10 holidays.
  • 401(k) with traditional and Roth options and a 4% match through Fidelity.
  • Minimal bureaucracy in a fast-moving, high-impact environment.

Interested in this position?

Apply directly on the company website

Apply Now

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