Applied ML Scientist

A globally leading technology company is looking for an Applied ML Scientist to design and evaluate next-generation machine learning and GenAI systems that power real-world applications. In this role, you’ll develop advanced LLM-based evaluation frameworks, prototype AI-driven solutions, and collaborate closely with cross-functional teams to bring cutting-edge research into production. If you’re passionate about building impactful ML systems and driving innovation at scale, we invite you to apply! Job Responsibilities :

• Design, develop, and evaluate advanced machine learning models and AI-driven evaluation systems (e.g., LLM-as-a-judge, automated evaluation frameworks) to enhance model performance and reliability.
• Prototype, test, and deploy scalable GenAI, LLM, and NLP / NLU solutions for real-world applications, ensuring strong alignment between research insights and production impact.
• Collaborate cross-functionally with research, product, and engineering teams to define requirements, identify opportunities for innovation, and translate business needs into technical solutions.
• Implement robust software engineering and MLOps practices to ensure reproducible and maintainable ML workflows. Minimum Qualifications :
• Strong foundation in machine learning fundamentals with the ability to tackle complex ML challenges.
• Experience or proven interest in designing and implementing AI-driven approaches to evaluation (e.g. LLM-as-a-judge, automated evaluation, etc).
• Demonstrated ability to develop high-impact language model systems for real-world applications.
• Expertise in GenAI, LLM, and / or NLP / NLU evaluation.
• Demonstrated ability to identify research directions, rapidly prototype solutions, and drive them to practical impact.
• Proficient in software engineering best practices (e.g., modular software design, testing).
• Strong proficiency in Python.
• Strong proficiency PyTorch, TensorFlow, or Jax.
• Excellent communication skills with a proven ability to engage diverse stakeholders.
• Experience with MLOps standards, including containerization, orchestration (e.g., Kubernetes), and CI / CD. Preferred Qualifications : Depth in one or more areas is acceptable; candidates are not expected to excel in every listed skill :
• Proven experience developing and owning high-impact, developer-facing systems and tools.
• Experience developing and evaluating complex agentic systems using LLMs.
• Experience adapting and aligning LLMs through various training strategies, e.g. continued pre-training, supervised fine-tuning, and reinforcement learning.
• Expertise in uncertainty estimation and calibration, active learning, or related problem spaces.
• Experience with ML platform design or ownership
• Hands-on experience with large-scale data processing frameworks, e.g. Spark, PySpark, Dask, or Ray.
• Track record of contributions to open-source ML projects or publications in top-tier ML conferences (e.g., NeurIPS, ICML, ACL). Type : Contract (W2) Duration : 12 months (with extension possible) Work Location : Seattle, WA (remote) Pay range : $100.00 - $ 120.00 / HR