לוח משרות דרושים, לחיפוש זה נמצאו 34,537 משרות

Were looking for a curious, analytical, and action-oriented Senior Product Analyst to join our Product Team. In this role, you will be the data leader within your product area, helping the team make data informed decisions, identify opportunities, and measure the impact of product initiatives.
Reporting into our GM, you will partner closely with Product Managers, Data Engineers, Business Intelligence Developers, and Software Engineers to turn complex data into clear insights that shape product strategy, roadmap decisions, and business planning.
You will play a key role in understanding how members interact with the Meds product, where we can improve their experience, and how we can better support their long-term success.
Responsibilities:
Partner with Product Managers and cross-functional stakeholders to support data-informed product decisions, roadmap planning, and business strategy.
Analyze user behavior, product usage, funnels, and engagement trends to identify opportunities to improve the member experience and product outcomes.
Build, maintain, and improve dashboards, reports, and alerts using business intelligence and analytics tools.
Define, track, and evaluate key performance indicators and reporting frameworks that help the business understand product performance.
Translate complex data sets into clear insights, actionable recommendations, and concise narratives for product, leadership, and business teams.
Design and analyze product experiments, including A/B tests, funnel analysis, and other methods that measure the impact of product changes.
Partner with Data Engineering, Business Intelligence, and Engineering teams to ensure data quality, reporting accuracy, and reliable measurement.
Proactively surface trends, anomalies, and risks in the data, bringing findings and recommendations to Product Managers and stakeholders ahead of requests, not just in response to them.
Define and build analytical frameworks to empower product and analytics teams with standardized, high-impact insight generation.
Define and build analytical frameworks to empower product and analytics teams with standardized, high-impact insight generation.

We're backed by tier-1 global VCs, led by second-time founders, and moving fast because the problem demands it. There are no silos here. No "that's not my area." If it ships, you own it.
We're hiring a full-stack software engineer who wants end-to-end ownership - backend, frontend, infrastructure touchpoints, and AI-driven workflows.
If you're looking for narrow scope or strict boundaries, this is not the role. If you like building real systems and taking responsibility for outcomes, read on.
What you'll do:
Own systems end-to-end - infrastructure, pipelines, and their behavior in production
Run and evolve our cloud infrastructure - Kubernetes, Kafka, Terraform, GitOps (AWS today, multi-cloud ahead)
Build the data backbone - ingestion, streaming, and pipelines into our lakehouse that stay correct and affordable as volume grows
Build AI-native engineering workflows: Sandboxes and dev environments, Automated verification and guardrails, Feedback loops that keep quality up as output scales.
Build golden paths - repo to production without a human bottleneck
Use Claude / Codex / AI copilots as default tools - not optional helpers
Debug production issues across the stack (no handoffs)
Ship fast, learn fast, fix fast
Take responsibility for what you build - including after it's live

We're backed by tier-1 global VCs, led by second-time founders, and moving fast because the problem demands it. There are no silos here. No "that's not my area." If it ships, you own it.
We're hiring a full-stack software engineer who wants end-to-end ownership - backend, frontend, infrastructure touchpoints, and AI-driven workflows.
If you're looking for narrow scope or strict boundaries, this is not the role. If you like building real systems and taking responsibility for outcomes, read on.
What you'll do:
Own features end-to-end - backend, frontend, APIs, and behavior in production
Build AI-native workflows:
Agent-driven actions
Human-in-the-loop interfaces
Explainability and control surfaces
Use Claude / Codex / AI copilots as default tools - not optional helpers
Work directly with product and customers to refine behavior
Debug production issues across the stack (no handoffs)
Ship fast, learn fast, fix fast
Take responsibility for what you build - including after it's live

We're backed by tier-1 global VCs, led by second-time founders, and already deployed with organizations operating at serious scale. AI is not a feature here - it's the system.
We're hiring a Senior AI Engineer to design, fine-tune, and operate AI agents and large-scale models in production. This role exists because off-the-shelf models aren't enough for the problems we're solving.
If you enjoy pushing models until they break - and then fixing them - keep reading.
What you'll do:
Design and operate AI agents that reason, act, and collaborate with humans
Fine-tune and adapt large language models for:
Behavior analysis
Reasoning over long, messy timelines
High-precision enterprise workflows
Build agent orchestration systems (tool use, memory, planning, feedback loops)
Run large-scale inference and training pipelines in production
Work on model evaluation, drift detection, and continuous improvement
Optimize for latency, cost, and reliability at real enterprise scale
Partner closely with DevOps, security, and backend engineers - no research silos
Ship models that are auditable, explainable, and safe in sensitive environments

Were seeking a Senior Machine Learning Engineer with strong MLOps abilities to own the production ML systems behind user engagement, cardiovascular risk stratification, and personalized health recommendations in the app. You'll build and run the CI/CD, real-time serving, versioning, and monitoring infrastructure that models depend on, working closely with data scientists who own the modeling to make sure what they build runs reliably at scale. You should have a proven track record of shipping ML systems to production and be comfortable using AI coding assistants as a core part of your workflow.
Responsibilities:
Build and own production ML infrastructure, including CI/CD pipelines, real-time model serving, model versioning and registries, automated evaluation pipelines, monitoring, and observability.
Serve models in real time at scale, with a strong focus on low-latency inference, reliability, and graceful degradation under load, and operate batch inference with clear standards for latency, availability, correctness, and cost.
Write high-quality, maintainable, well-tested production-grade code, and own its observability, debugging, reliability, and scalability in production.
Implement model monitoring for drift, data quality, latency, and performance degradation, with automated retraining.

Were seeking a talented and impact-driven Senior Data Analyst, Product to join our ML team. In this role, you will shape the future of the digital health products that help people understand and improve their heart health. By applying your technical skills, analytical mindset, and product intuition to rich real-world health and behavioral data, you will help define the experiences we build for our users and the value we deliver to employers and health plans.
You will collaborate with a wide range of cross-functional partners across Product, Engineering, Data Science, Data Engineering, Clinical, Marketing, and Customer Success. You will use data and analysis to identify and solve our biggest product challenges, influence product strategy and investment decisions, and translate insights into digital solutions that improve the well-being of the people we serve.
What you'll do:
Product leadership: Use data to shape product development, quantify new opportunities, and identify upcoming challenges. Help your partner teams prioritize what to build, set goals, and understand their product's ecosystem, ensuring what we build brings real value to users, clients, and us.
Analytics: Guide teams with data and insights. Develop hypotheses and test them using a varied toolkit of rigorous analytical approaches, from experimentation to causal inference and statistical modeling.
Communication and influence: Don't just present data, tell data-driven stories. Influence partners with clear insights and recommendations, and become a trusted strategic partner through structure and clarity.
Your responsibilities:
Work with large and complex datasets, applying statistical analysis and visualization methods to extract meaningful patterns and trends.
Identify and measure the success of product efforts through goal setting, forecasting, and monitoring of key product and engagement metrics.
Design, execute, and analyze A/B tests, including tests of ML-driven features, accounting for cause/effect and treatment/prevention relationships.
Monitor and analyze the performance of our ML models in production, and generate insights and research leads for model improvements and new data-driven solutions.
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
Partner with Product, Engineering, Data Science, and healthcare professionals to inform and execute product strategy.
Integrate AI tools into your workflows to drive measurable gains in efficiency and quality.
Stay current with the latest research and best practices in healthcare analytics and AI.

We are looking for a motivated Junior data Engineer to join our data engineering team. In this role, you will support the development, maintenance, and improvement of data pipelines and infrastructure that power our AI department. This is a great opportunity for someone early in their career who is eager to learn modern data technologies and contribute to data -driven solutions in a production environment. Key Responsibilities
* Assist in building, maintaining, and improving ETL /ELT pipelines for data processing.
* Work with modern data tools and platforms, including Databricks (Spark, SQL) Apache Airflow, and Azure services
* Support troubleshooting of data pipelines, queries, and scheduled jobs to improve reliability and performance.
* Help implement and follow best practices for data governance, security, and monitoring.
* Collaborate with senior team members to deliver scalable and efficient data solutions.
* Stay current with data engineering tools, technologies, and best practices.

We are the leading AI creation platform helping teams build, deploy, and scale their content output by combining all the leading AI models, AI tools, and a world-class stock catalog in one place. Plus, with a dedicated partnership from our award-winning creative team, organizations have everything they need to succeed with AI today. Trusted by 50M+ creators and 50% of Fortune 100 companies worldwide including Google, Amazon, Microsoft, and Versace, we provide a seamless, subscription-based platform with a global license to produce professional video content efficiently and securely. We are looking for an IT & AI Operations Specialist who will not only maintain and elevate our corporate IT environment, but also pioneer internal AI automation, empowering our global teams to work faster and smarter. In this role, you will bridge traditional corporate IT infrastructure with modern, cutting-edge AI workflows. You will manage IT operations, identity controls, and SaaS ecosystems while active identifying, implementing, and maintaining AI agents, automation tools, and internal productivity pipelines across HR, Marketing, Support, and Finance. Key Responsibilities
* IT Operations & Infrastructure: Manage corporate devices, user onboarding/offboarding, SaaS licenses, hardware procurement, and endpoint management (MDM, Jamf, Intune).
* Identity & Access Management: Oversee identity access controls, SSO/SCIM integrations, Okta/Google Workspace, and system permissions across the organization.
* AI Workflow Automation: Design, build, and deploy automated internal workflows and AI assistants/agents to eliminate operational friction across non-technical teams.
* AI Tool Evaluation & Implementation: Scout, TEST, and onboard emerging generative AI products, LLM frameworks, and productivity tools into company-wide workflows safely.
* Standardization & Governance: Establish reusable prompt libraries, integration templates, and AI usage policies so teams can safely build their own minor automations.
* Support & Troubleshooting: Provide Tier 2/3 Technical Support for complex hardware, software, network, and AI-tooling issues.