Top Tech Jobs & Startup Jobs

Provides full-cycle HR support across multiple early-stage life sciences companies during a five-month leave coverage period. Responsibilities include onboarding, performance management, employee relations, offboarding, HRIS administration, compensation benchmarking, job leveling, offer structuring, compliance, and HR coordination. The role requires independent prioritization across organizations, strong knowledge of multi-state employment law, confidential data management, and experience building HR infrastructure in startup environments.

Design, build, and own scalable data infrastructure for proteomics research and machine learning. Responsibilities include developing production data platforms and pipelines, integrating instruments and LIMS, creating cloud infrastructure with infrastructure-as-code and CI/CD, ensuring data integrity and lineage, and transforming raw experimental data into reliable ML-ready datasets. The role partners closely with scientific teams, establishes engineering standards, sets technical direction, and mentors colleagues.

Lead product strategy and execution for Iris Chat, an AI-powered psychological fitness product. Own product vision, customer journeys, activation, retention, conversion, subscription value, experimentation, and AI quality. Manage product, design, engineering, and AI research teams; hire and develop leaders; balance research and delivery; and establish standards for evaluation, privacy, safety, reliability, and user trust. Partner with leadership to build a focused roadmap and durable consumer business.

Develop evolutionary algorithms for autonomous scientific discovery, enabling populations of models, hypotheses, programs, and representations to evolve through iterative search, selection, evaluation, and recombination. Build Bayesian and probabilistic methods for candidate ranking, uncertainty estimation, diversity preservation, and quality measurement. Establish benchmarks, integrate algorithms into autonomous-science pipelines, publish research, guide technical direction, and mentor colleagues as a senior individual contributor.

Lead full‑stack development of customer‑facing features, own product lifecycle from design to release, build scalable AI‑enabled back‑end systems on AWS, improve CI/CD and testing, collaborate with product, design, and ML researchers, and ensure security and privacy best practices.

Leads product safety and wellbeing strategy for AI-powered experiences. Owns safety roadmaps, guardrails, evaluation frameworks, benchmarks, metrics, monitoring, launch-readiness criteria, and human or automated evaluation programs. Assesses failure modes and emerging risks, including self-harm and crisis scenarios, and translates expert and user findings into product guidance. Partners with engineering, machine learning, product, design, and data science teams to improve risk detection, response generation, escalation, and user experience.

Develop and deploy LLM-powered ML applications for psychological wellbeing. Collaborate with psychologists to translate insights into computational systems, advance RLHF and agentic AI methods, build scalable data and training pipelines, integrate ML systems into real-world products, and communicate results to multidisciplinary teams.

Own international accounting, compliance, financial close, statutory reporting, audits, tax filings, consolidations, and intercompany transactions for multiple subsidiaries. Manage outsourced providers, support UK equity compensation and international billing, coordinate new entity setup, and oversee financial reporting for a government contracting entity. Partner with Legal, HR, Treasury, Tax, Compensation, portfolio companies, auditors, and government-contracting advisors across jurisdictions.

Develop and integrate fixed-wing UAV systems spanning autopilot firmware, airframes, propulsion, electronics, C2 links, ground station software, and scientific payloads. Responsibilities include modifying ArduPilot source code, tuning flight systems, conducting flight tests, analyzing logs, designing PCBs, ensuring spectrum compliance, troubleshooting field deployments, and documenting engineering processes for a scalable, field-ready platform.

Leads the design, implementation, and optimization of cloud-native data infrastructure, platforms, storage solutions, and complex data pipelines. Establishes engineering standards for testing, monitoring, releases, and reliability; troubleshoots cross-system failures and leads incident reviews. Partners with infrastructure, laboratory IT, data science, bioinformatics, and scientific teams to deliver secure, scalable solutions. Mentors engineers, guides technical initiatives, and uses generative AI to accelerate development and data transformation.