Trust & Safety ML Engineer safeguarding Hapiko’s generative - AI sticker printer for children. Owning moderation pipelines, safety evaluations, classifiers, red teaming, and compliance systems.
About the role
- Senior ML Engineer advancing innovation in small language models for League's healthcare platform. Focused on research and engineering in model development and applied AI systems.
Responsibilities
- Design and implement experiments across fine-tuning, distillation, and optimization of small language models (1–10B parameters)
- Rapidly prototype and evaluate new approaches to model performance, efficiency, and reasoning quality
- Leverage modern tooling and AI-assisted workflows to accelerate iteration cycles
- Build applied systems that connect models, data pipelines, and evaluation frameworks
- Focus on “wiring together” components across model training, evaluation, and deployment workflows
- Collaborate with engineering teams to transition promising experiments into production environments
- Contribute to training data design, including curation, labeling strategies, and synthetic data generation
- Work with data partners to explore AI-driven insights and improvements to model performance
- Define and run experiments to assess model performance across accuracy, reasoning, and safety dimensions
- Contribute to building lightweight evaluation frameworks and benchmarking approaches
- Actively leverage AI tools (e.g., Copilot, LLM-assisted coding, research copilots) to improve productivity and experimentation speed
- Document and share workflows that improve how the team builds and evaluates models
- Partner with Product, Platform Engineering, and AI Orchestration teams to integrate models into real-world use cases
- Communicate complex technical concepts clearly to cross-functional stakeholders
Requirements
- 5+ years of hands-on experience in applied ML/AI engineering, with a focus on language model development, fine-tuning, or NLP systems.
- Proven track record shipping fine-tuned or distilled LLMs/SLMs (1–10B parameters) to production.
- Deep expertise in PEFT techniques — LoRA, QLoRA, adapter tuning — and model quantization and distillation pipelines.
- Hands-on experience with RLHF/RLAIF, reward modeling, or safety alignment workflows.
- Strong background in data curation, labeling pipeline design, and synthetic data generation.
- Proficiency with model training frameworks and tooling: NeMo, Hugging Face Transformers, Axolotl, or equivalent.
- Experience with model serving stacks: vLLM, Triton, or similar; familiarity with inference optimization techniques.
- Comfort operating on cloud infrastructure (GCP, Vertex AI, AWS) and with GPU resource management.
- Solid understanding of healthcare data privacy and safety requirements: HIPAA, FHIR, clinical ontologies.
- Demonstrated ability to define and own evaluation frameworks — not just build models, but know whether they're working.
- Strong technical communication skills; able to present complex model decisions clearly to cross-functional and executive audiences.
- Bachelor's or graduate degree in Computer Science, Machine Learning, or equivalent experience.
Benefits
- Health insurance
- Flexible remote days
- Professional development opportunities
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
Senior Data Engineer building cloud - native data and ML platforms for Hive.co’s event - marketing automation products. Owning pipelines, model infrastructure, and audience - data systems at scale.
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s AI - native omnichannel retail brands. Deploying machine learning that improves pricing and other commercial decisions.
Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
New - grad software engineer building Quora’s distributed ML platform, model serving, and developer tooling. Supporting Quora’s global knowledge - sharing product with scalable GPU infrastructure.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Senior Machine Learning Engineer building conversational AI agents and production ML systems. Helping Numa automate automotive dealership service and sales through evaluation - first tooling and infrastructure.