דרושים » הנדסה » Data Science Engineer

As an AI Developer on our Optimization team, you will play a key role in advancing our core optimization capabilities by infusing them with cutting-edge artificial intelligence.

Our team is on a mission to significantly enhance our existing, high-performance optimization engine. You'll tackle a diverse range of complex problems - including optimization of vehicle routing and scheduling - for our customers at a massive scale.

You will join our team at a pivotal moment and be an integral part of building our next-generation AI/ML capabilities from the ground up. As a key contributor, your responsibilities will span the entire model lifecycle, from augmenting our current optimization models with advanced AI to implementing the infrastructure for their deployment and monitoring.

You will apply state-of-the-art techniques such as Deep Reinforcement Learning (DRL), predictive analytics, and Graph Neural Networks (GNNs), all while working with rich datasets including Geographic Information System (GIS) data.

Another core part of your role will be implementing best practices for safe AI/ML rollouts. You will help build and maintain robust A/B testing frameworks and canary deployment strategies, ensuring our innovations reach production safely and effectively.

In this highly collaborative position, you will work closely with other engineers and scientists, as well as cross-functional product teams in the US, to bring these intelligent services to life.

Responsibilities:

Develop, implement, and deploy state-of-the-art optimization models and machine learning algorithms to solve complex business problems like vehicle routing and resource scheduling.

Design and build robust, end-to-end MLOps pipelinesfrom data ingestion and feature engineering to model training, validation, and serving in a production environment.

Translate complex scientific concepts and research papers into production-quality code, primarily using Python and leveraging frameworks like PyTorch and optimization libraries.

Conduct rigorous offline and online experiments to validate model performance, ensuring that solutions are statistically sound, reliable, and deliver measurable business impact.

Shape the Future of Cybersecurity with Us Are you driven by curiosity, innovation, and the desire to turn cutting-edge research into real-world impact? Join us, an established but rapidly growing cybersecurity startup, where you'll be part of a small, elite team building groundbreaking AI-powered security products from the ground up. Work alongside top minds in security research, R&D, product, and data engineering to drive innovation and create real value for global customers. This is your chance to contribute to a foundational mission - developing AI technology that proactively protects against todays most sophisticated cyber threats.

What will you do:
As an ML Engineer, youll play a central role in shaping our future technology. Youll: Own AI product creation end-to-end - from the initial concept through building prototypes to full-scale production. Drive innovation by developing and integrating ML and Generative AI solutions into our core cybersecurity products: Endpoint, XDR, Network Detection, and Posture Management. Analyze massive volumes of security data to uncover hidden patterns, threats, and insights. Develop and fine-tune models with state-of-the-art optimization strategies and performance metrics. Contribute to and expand our AI infrastructure, including data pipelines, evaluation tools, and deployment frameworks. Conduct rigorous experimentation, explain and monitor the real-world performance of your models. Write production-ready code that makes it into our deployed AI systems.

As a Data Scientist at our company, you will play a critical role in developing data-driven solutions that uncover legal insights at scale. Youll work across domains-analyzing large and complex datasets, designing models (including those based on LLMs), and translating data into actionable insights that support our mission of surfacing justice.
Youll take full ownership of your analyses and models, from problem definition to experimentation and evaluation. Youll collaborate closely with engineers, domain experts, and product teams to design robust data science solutions that create real-world impact and inform product decisions.
Responsibilities:
Design and implement data science solutions using LLMs and legal datasets to surface insights and automate tasks.
Lead end-to-end development of ML pipelines-from data exploration and preprocessing to model training, deployment, and monitoring.
Build and maintain production-ready pipelines for experimentation, evaluation, and inference.
Collaborate with legal stakeholders and analysts to define problems, identify opportunities, and translate them into data-driven solutions.
Develop and iterate on LLM-based systems, including prompt engineering.
Write clean, maintainable Python code that meets production standards, including testing and documentation.
Stay curious and proactive-evaluating new tools, approaches, and technologies.
Communicate clearly across technical and non-technical audiences, contributing to a collaborative team culture.

as a data scientist, you will harness your skills to help millions of individuals and organizations fend off any malicious activity - practically defending the world from evil : )
Collaborate with brilliant security researchers, data scientists, and engineers to create new security capabilities for some of our key products. We are looking for a team player who is also independent, curious, and willing to share their perspective and push their ideas.
In this position, you will:
Lead end-to-end data science projects from research exploration to production.
Engage with cutting-edge GenAI technology to develop innovative solutions and enhance our data science capabilities.
Design and implement improvements of current ML-based products.
Work with domain experts to help shape the right questions and use your analytical skills to answer them.
Find new and innovative approaches to turn the huge data-stream created by our platform into additional security value.

As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our companys next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code modelsoptimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

This is a senior leadership role focused on technical excellence and innovation. You will mentor a talented team of engineers and scientists, guide the end to end technical strategy from innovative research to production deployment and ultimately define the art of the possible for our most critical operational systems.

Responsibilities:

Lead the design and architecture of complex, end to end AI systems, guiding projects from initial conception and research through to production deployment and impact analysis.

Own the technical vision for the next generation of intelligent automation, creating patented technologies that directly impact Salesforce Field Service's core competitive advantage and market differentiation.

Provide technical leadership and set the strategic direction for the research and development of novel optimization and machine learning solutions.

Drive fast paced experimentation by independently or collaboratively prototyping solutions that showcase how new AI technologies can address real world business challenges. Collaborate with cross functional teams to translate prototypes into actionable solutions and define incremental delivery plans for implementation.

Mentor and guide a team of AI developers and scientists, fostering a culture of innovation, technical excellence, and continuous learning.

Stay at the forefront of academic and industry advancements by attending top tier conferences, networking with experts, and continuously learning about the latest in optimization, AI, and large language models (LLMs) to identify, evaluate, and apply emerging techniques that drive a significant competitive advantage.
JR314441

We are looking for an ML Engineer to join our Data department. In this role, you will be responsible for the infrastructures needed to train models, serve them and do other ML magic.
What Youll Do:
Develop, integrate and optimize end-to-end ML solutions (data pipelines, training workflows, and serving infrastructure)
Plunge into a world of data, analytics, ML, high-paced and high-scale user and market movements
Work closely with Data Scientists to understand the business from top-to-bottom and turn their dreams into reality

If you're looking for an exciting opportunity to make a significant impact and grow with a passionate team, we are the place to be.
Your Role: Drive, Build, and Shape:
Build Scalable Solutions: Lead the design and development of robust, scalable systems using a mix of cutting-edge languages, frameworks, and technologies, while maintaining a strong focus on quality and performance.
Customer-Centric Development: Collaborate with customers and stakeholders to understand their needs, ensuring the team delivers high-value solutions aligned with mission.
Cross-Functional Collaboration: Work closely with cross-disciplinary teams, including DevOps, data engineering, and product management, to align on priorities and drive company-wide initiatives.
Foster Growth: Cultivate an environment where team members are empowered to innovate, take ownership, and expand their skill sets.

Shape the Future of Data - Join our mission to build the foundational pipelines and tools that power measurement, insights, and decision-making across our product, analytics, and leadership teams.
Develop the Platform Infrastructure - Build the core infrastructure that powers our data ecosystem including the Kafka events-system, DDL management with Terraform, internal data APIs on top of Databricks, and custom admin tools (e.g. Django-based interfaces).
Build Real-time Analytical Applications - Develop internal web applications to provide real-time visibility into platform behavior, operational metrics, and business KPIs integrating data engineering with user-facing insights.
Solve Meaningful Problems with the Right Tools - Tackle complex data challenges using modern technologies such as Spark, Kafka, Databricks, AWS, Airflow, and Python. Think creatively to make the hard things simple.
Own It End-to-End - Design, build, and scale our high-quality data platform by developing reliable and efficient data pipelines. Take ownership from concept to production and long-term maintenance.
Collaborate Cross-Functionally - Partner closely with backend engineers, data analysts, and data scientists to drive initiatives from both a platform and business perspective. Help translate ideas into robust data solutions.
Optimize for Analytics and Action - Design and deliver datasets in the right shape, location, and format to maximize usability and impact - whether thats through lakehouse tables, real-time streams, or analytics-optimized storage.
You will report to the Data Engineering Team Lead and help shape a culture of technical excellence, ownership, and impact.

Required Principal Data Scientist - LLM/GenAI (Cortex)
Your Career
Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin.
Your Impact
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach
Design and implement LLM-based solutions to face modern cybersecurity challenges
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.