דרושים » תוכנה » AI scientist- Foundational Models and Agentic systems

Are you a senior AI researcher who thrives at the intersection of cutting-edge computer vision and real-world impact? Do you combine deep research expertise with the engineering instincts to ship models that work in production? Join the Content team within our AI group, where youll lead applied research initiatives that transform how sports content is created and experienced.

This is an applied research role with a strong ownership mandate - youll drive the full research lifecycle from problem framing and experimental design through to production integration.

We are dedicated to revolutionizing sports production. Our AI-powered solutions automatically capture sports events and transform them into personalized content, turning key moments into engaging experiences for players, teams, and fans. As a Senior AI Research Scientist, you will have direct impact on the companys innovation roadmap, leading core AI capabilities that power our platform at scale.

As part of your role, you will:
Own the research lifecycle end-to-end: problem definition, literature review, experimental design, model development, evaluation, and production integration.
Design, implement, and evaluate state-of-the-art deep learning models for computer vision tasks including detection, tracking, event recognition, and temporal modeling in video.
Drive applied research projects with clear product impact - not just experimentation, but shipping models that run reliably in production.
Collaborate closely with ML engineers, infrastructure engineers, and QA to ensure smooth model integration and performance in real-world conditions.
Contribute to our research culture: present findings internally, propose new research directions, and stay at the forefront of computer vision and deep learning.
Influence architectural decisions around model design, data pipelines, and evaluation frameworks.

A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities.

This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization.


Responsibilities:

Lead and mentor a global team of Data Scientists.

Define and execute the company's Data Science strategy.

Drive the development of advanced machine learning, optimization, and forecasting solutions.

Partner closely with Product, Engineering, Customer Success, and executive leadership.

Translate complex business challenges into scalable analytical solutions.

Support customer-facing initiatives and strategic engagements when needed.

Establish best practices for experimentation, model evaluation, and performance measurement

Act as a key stakeholder in shaping the company's AI vision and roadmap

As a Data Science Manager, you will lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions. You will own the end-to-end development lifecycle of AI projects, from exploratory research and experimentation through to scalable deployment and optimization. In this role, you will partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery. You will also drive innovation across a broad spectrum of ML domains, including supervised/unsupervised learning, anomaly detection, and generative AI, while providing hands-on guidance and championing best practices in MLOps, data governance, and model evaluation.
Key Responsibilities
Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

We're looking for a Senior AI Solutions Builder to join our Product team. In this role, you will design, build, and ship AI-powered solutions that enhance productivity and drive measurable business value across the organization.

You will operate at the intersection of AI, data, pricing and business - owning the end-to-end development of agents, copilots, and workflow automations that directly inform decisions and eliminate manual work.

You are both a builder and an enabler. You ship solutions yourself and raise the AI capability floor for the teams around you. You'll collaborate closely with Product, Engineering, CS, Sales, and builders across the company to deliver outcomes that improve decision velocity, product and operational efficiency, and long-term growth.

You Will
Design and ship AI-powered copilots, agents, and decision-support tools for the Product team, starting with Pricing

Build data pipelines and analytical models for pricing intelligence

Develop autonomous agents that automate recurring Product tasks

Automate manual workflows across product tools so the right action happens when a signal fires

Build LLM-based scoring models that give roadmap and prioritization decisions a data backbone

Enable and upskill product teams through AI playbooks, sessions, and hands-on co-building

Collaborate with builders across Engineering, CS, GTM, and other teams to co-create solutions that scale

Define and track impact: time-to-insight, decision velocity, manual hours eliminated, and business outcomes

We're looking for a Data Scientist to turn our network data into a competitive advantage. You'll work directly with terabytes of telecom signaling, session, and usage data to build models that improve network selection, detect anomalies, optimize cost-per-gigabyte, and surface insights that shape product and commercial strategy. This is a high-impact role sitting at the intersection of ML, telecom engineering, and business decision-making.

What You'll Do

Design and deploy machine learning models on network data - including network selection optimization, churn and usage prediction, fraud and anomaly detection, and QoS/QoE forecasting.

Analyze CDRs, signaling events (Diameter, GTP, SIP), session logs, and radio-level metrics to identify performance issues, cost drivers, and growth opportunities.

Partner with the Network Operations and Product teams to translate raw telemetry into actionable signals - e.g., which carrier to steer traffic to in a given country at a given hour.

Build forecasting and segmentation models that inform pricing, capacity planning, and customer lifecycle strategy.

Own analyses end-to-end: framing the business question, exploring the data, building the model, validating it, and communicating findings to both technical and executive audiences.

Define and track KPIs for network quality, customer experience, and commercial performance, and build dashboards that make those metrics visible across the company.

Mentor junior data scientists and analysts, and help raise the bar on data science practices, code quality, and experimentation rigor.

We're looking for an experienced AI Security Architect to join the Security Architecture team.
As a AI Security Architect, you'll design and govern enterprise AI security frameworks, define controls for AI/ML platforms and LLM deployments, and drive secure AI adoption in close collaboration with engineering, business units, and data teams.
You'll own security architecture reviews, threat modeling, and risk assessments across the full AI lifecycle - from development through production.
Key Responsibilities:
Design, develop, and maintain enterprise AI security architectures, frameworks, standards, and policies
Define and implement security controls for AI/ML platforms, LLM deployments, AI-enabled applications, and supporting infrastructure
Establish security requirements and best practices for AI development, deployment, and operational processes
Assess AI-related risks and ensure alignment with corporate security standards, regulatory requirements, and industry best practices
Collaborate with IT, cloud, data, and security teams to ensure secure deployment of AI solutions across the organization
Familiarity with AI coding assistants, autonomous agents, LLM frameworks, and orchestration systems

Do you want to join an international team within an innovative fast-paced medical device company? Grab the opportunity and make good use of your Mathematical and programming skills and affinity to medical device.

Key Responsibilities
You will deal with imaging, 3D modeling, surface reconstruction, image processing and high-performance computing.
You will understand the products and the customer needs.
You will research and analyze the underlying problems using real data.
Design and test algorithms in C++ and Python.
Implement algorithms in C++, and integrate them into the application.
Work closely with other members of the algorithms team and members of other groups such as physics and electronics.
Participate in design reviews and code review of co-developers.

We're a small, fast, high-ownership team, and we're looking for a Senior Backend Engineer to make work for agents - both by building new agent-facing infrastructure and by reshaping our existing platform for a world where the caller is a machine. Some of this is greenfield. Much of it is taking APIs, auth, and SDKs and making them ergonomic, legible, and reliable for agents.

Its a problem the whole industry is still figuring out. Youll help define what great API design looks like when the caller is not a human developer, but an agent acting on their behalf.

What you'll do
Build the surfaces agents call directly: API-first account provisioning, machine-to-machine authentication, scoped credentials, and agent-level identity and attribution.
Own our MCP (Model Context Protocol) servers and an agent-first CLI - let coding agents and LLMs discover and invoke reliably, engineered for agentic callers: token-efficient tool schemas, machine-parseable output, and loud, actionable failures instead of silent ones.
Harden the agent media path - make upload and core media operations reliable for non-human callers, eliminating the ambiguity and silent-failure modes that cause agents to drop off mid-task.
Make agent behavior measurable - partner on the instrumentation, signals, and attribution that tell us whether agents are succeeding.
Work across a polyglot backend - Node.js/TypeScript for the agent tooling layer, with Ruby/Rails and Go in the core platform.
Ship, measure, iterate - prototype quickly, dogfood the experience, and represent the agent's perspective in every design decision. Work closely with Product, Ecosystem, and Discoverability across the AX team.