A Technical Product Manager role focused on ensuring Medley’s AI-powered instructional scaffolds meet high standards for quality and user experience. The role sits at the intersection of pedagogy and AI product work.
Responsibilities
Define what 'excellent' looks like by translating research-based practice in literacy, special education, and multilingual learner instruction into clear quality standards.
Track and monitor quality with a robust evals system, building and maintaining datasets, rubrics, and eval suites.
Conduct regular error analysis and trace review using human labeling, LLM-as-judge, and rule-based evals.
Refine prompts and models; write, test, and run model comparisons and regression tests.
Review signals from educators, data from support tickets, and product analytics to inform product decisions.
Perform hands‑on laboratory testing of electronic and security technologies, develop software and controls, and apply data analysis to support defense and government clients.
Compensation
Salary Range USD $140,000.00 - USD $154,000.00 /Yr.
Responsibilities
Performing hands‑on laboratory testing of electronic devices and security technologies using instruments such as oscilloscopes, protocol analyzers, and RF equipment
Developing software in Python, LabVIEW, and other tools to automate tests, control instruments and hardware, acquire data, and build repeatable analysis pipelines
Supporting engineering projects as needed with prototyping custom fixtures, instrumentation, and data acquisition setups, systems integration, controls, thermal analysis, and mechanical design
Analyzing results with statistical methods and error analysis, visualizing and documenting them in clear, traceable technical reports, troubleshooting equipment, test setups, and data to root cause, and communicating findings to colleagues and clients
Building the practice by staying current in laboratory testing, security, and data practices, supporting marketing of its capabilities, and educating fellow consultants
Requirements
Ph.D. OR Masters plus 3+ years’ experience in Physics, Nuclear Engineering, Electrical Engineering, or a related experimental science or engineering field
Lead end‑to‑end deployments of AI models in life sciences organizations, designing production systems and ensuring regulatory compliance.
Responsibilities
Design and ship production systems around models, owning integrations, data provenance, reliability, and on‑call readiness across research, clinical, and operational workflows.
Lead discovery and scoping from pre‑sales through post‑sales, translating ambiguous workflow needs into hypothesis‑driven problem framing, system requirements, and an execution plan with measurable endpoints.
Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until sustained production impact is demonstrated.
Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.
Run evaluation loops that measure model and system quality against workflow‑specific scientific benchmarks and use results to drive model and product changes.
Requirements
PhD
MS
equivalent applied experience in a life sciences relevant field
Lead research and evaluation of clinical AI systems, providing technical guidance to regulatory affairs and driving reusable evaluation assets.
Compensation
The annual base pay for this position ranges from $ 124 713,60 - 187 070,40 USD Annual. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Design and run evaluations of LLM-based and agentic clinical systems
Build reusable evaluation assets such as test sets, scoring rubrics, annotation protocols
Study AI output impact on clinical judgment through expert-agreement and user studies
Investigate failures using traces, logs, qualitative review, and quantitative analysis
Publish and communicate findings internally and externally
Requirements
PhD in Machine Learning, Computer Science, NLP, Information Science, Biomedical Informatics, Statistics, or a related quantitative discipline
Develop machine‑learning and AI solutions to improve safety, reliability, and operational efficiency of Microsoft 365 services, focusing on scenario health gating.
Compensation
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Responsibilities
Scientific problem formulation and algorithm development
Translate service-health and change-safety problems into scientific objectives, hypotheses, datasets, baselines, and success metrics
Develop and evaluate machine‑learning, statistical, causal, time‑series, or agent‑based methods for regression detection, risk estimation, failure attribution, and gating decisions
Compare technical alternatives and explain tradeoffs involving accuracy, interpretability, latency, scale, cost, reliability, and customer risk
Address noisy, sparse, delayed, imbalanced, and distribution‑shifted production data
Requirements
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Senior Scientist, Clinical AI Research & Evaluation (Regulatory & Responsible AI)
Lead AI research and evaluation for clinical AI systems, providing technical guidance to regulatory affairs and building reusable evaluation assets.
Compensation
The annual base pay for this position ranges from $ 124 713,60 - 187 070,40 USD Annual. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Design and run evaluations of LLM-based and agentic clinical systems
Build reusable evaluation assets
Study AI output impact on clinical judgment
Investigate failures and translate findings into improvements
Publish and communicate findings
Requirements
PhD in Machine Learning, Computer Science, NLP, Information Science, Biomedical Informatics, Statistics, or a related quantitative discipline
Lead the development and automation of biophysical and biochemical assays to support Design‑Make‑Test‑Learn workflows in discovery.
Compensation
The anticipated base pay range for this position is:
€63 700,00 - €109 480,00
Responsibilities
Design, develop, and execute SPR and biochemical assays to support hit validation and lead optimization
Generate and interpret kinetic, affinity, thermodynamic, and biochemistry data to guide SAR and critical project decisions
Deliver high‑quality biophysical and biochemistry data that accelerates DMTL cycles and enables rapid, data‑driven discovery decisions
Develop robust and scalable experimental workflows that expand throughput and reproducibility across the portfolio
Drive the development and implementation of automated biophysical and biochemical lab design and workflows that increase experimental scale, consistency, and scientific impact
Requirements
Ph.D. in Biophysics, Biochemistry, Structural Biology, or a related scientific discipline
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