דרושים » תוכנה » Machine Learning Engineer

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of ML engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Required Machine Learning Engineer II - GenAI Applications
26947
About the team:
This opening is for the GenAI Applications Team within the Data & AI Marketplace department.
The GenAI Applications team is responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and trip helpfulness. The team builds AI-driven applications and conversational agents, such as chatbots and intelligent assistants, that significantly enhance the end-to-end customer experience.
Role Description:
As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouraged-this role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.

we are looking for a AI Engineer to join our R&D organization and help lead the development of AI-powered and data-driven capabilities in our Developer Productivity Platform.
In this role, you will transform data into actionable insights and intelligent models that help software teams understand, measure, and improve how they work. Youll work closely with product, data, and engineering teams to design and deliver AI and data science solutions that have real impact on developer productivity and business outcomes.

Key Responsibilities:
Design, develop, and deploy AI-driven features & data science and ML models to analyze code flows, software development processes, team behaviors, and performance metrics.
Build AI & data pipelines and analytical infrastructure that ensure data quality, accessibility, and freshness at scale.
Translate complex data into clear, actionable insights and code analysis that influence product direction and drive customer value.
Develop and maintain predictive, prescriptive, and diagnostic models to support use cases like delivery forecasting, productivity measurement, and team health analysis.
Partner with Product Managers, Data Engineers, and Backend Engineers to bring insights to life through AI & data-driven features and platform improvements.
Monitor and continuously improve model performance through experimentation, A/B testing, and user feedback loops.
Research and evaluate new AI/ML tools and methodologies to enhance the platforms intelligence and scalability.

Required Senior Machine Learning Engineer I - GenAI Applications
20031
Leadership/Team Quote:
This opening is for the GenAI Infra team in the Marketplace AI department.
The GenAI Infra team builds the Agents platform which is used for all agnetic and non-agentic flows. This team is responsible for both the GenAI agents and the orchestration around them, helping support applications such as the AI Trip Planner, Free text search, etc.
Role Description:
As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Required Machine Learning Performance Engineer
Description
Our team is responsible for the AWS Neuron software stack, which powers Generative AI and other advanced ML workloads on AWS's custom-built ML accelerators Inferentia and Trainium. These accelerators deliver best-in-class performance and cost-efficiency for ML inference and training in the cloud.
We're building a new core group of engineers in TLV (Tel Aviv) to drive innovation in ML systems performance and software. As a Machine Learning Performance Engineer, you'll help shape the direction of the team from the ground up and work on:
Optimizing system performance across the entire ML software stack
Analyzing high-performance ML workloads running on Annapurna hardware
Developing high-performance kernels for critical ML operations
Enhancing the Neuron SDK to improve developer experience and system capabilities
Collaborating across Compiler, Frameworks, and Hardware teams to maximize end-to-end performance
As part of the Performance Engineering Team, you'll contribute to projects involving instruction scheduling, memory management, parallelism, kernel optimization, and compiler enhancements to maximize end-to-end performance.
This is a unique opportunity to be at the intersection of ML and systems within AWS, helping to build the future of AI infrastructure right here in Tel Aviv.
Key job responsibilities
Our engineers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base. You will:
Solve challenging technical problems, often ones not solved before, at every layer of the stack.
Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
Research implementations that deliver the best possible experiences for customers.
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, youll create metrics, implement automation and other improvements, and resolve the root cause of software defects. Youll also:
Build high-impact solutions to deliver to our large customer base.
Participate in design discussions, code review, and communicate with internal and external stakeholders.
Work cross-functionally to help drive business decisions with your technical input.
Work in a startup-like development environment, where youre always working on the most important stuff.
Considering the technical requirements of this role, and to ensure fair and equal candidate consideration, we are conducting full interview loops. If you meet the basic qualifications, and the team is interested in moving forward, we will be in touch to coordinate your interviews.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.

We are looking for a Machine Learning Tech Lead to promote machine learning engineering excellence. Someone who is passionate about building scalable, high-quality data products and processes, while ensuring production systems maintain strong real-time performance observability.

As a Tech Lead on the ML team , you will focus on designing and maintaining the core infrastructure that empowers the Machine Learning Engineers working within Data Science product teams. Youll collaborate closely with stakeholders across data science, product, and engineering, playing a pivotal role in driving the business by architecting and enabling the infrastructure for machine learning model development, serving, and lifecycle managementthe foundation of our product.

Responsibilities:

Partner with MLEs in Data Science product teams and key stakeholders to design and maintain infrastructure for:
Data wrangling supporting and enabling data requirements for research, training, validation, and testing.
End-to-end ML delivery enabling model performance development, training, validation, testing, and version control.
Drive engineering best practices including code and model versioning, CI/CD pipelines, rollout strategies, and disaster recovery procedures.
Build and support monitoring and observability tools dashboards, alerts, and performance tracking of models in production.
Lead architecture projects such as:
Feature Store centralizing feature engineering and serving across teams.
Vector Databases enabling large-scale embedding storage and retrieval for advanced ML applications.
GPU Cluster Scaling optimizing distributed training and inference infrastructure.
Collaborate with product, data science, and engineering teams to solve complex problems, identify trends, and create opportunities through robust ML infrastructure.

Description
For many of us theres that one podcast we never miss, and video content is part of our daily routine, whether its professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at our company, we know it well. Thats exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.
our companys technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.
About the Innovation Team
At our company, the Innovation team is all about pushing the limits of AI to transform content creation. We work on everything from enhancing audio and video quality to automating production with machine learning, NLP, and computer vision. Whether its real-time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If youre excited about shaping the future of media tech, youll fit right in.
On your day to day
Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.
As a hands-on team lead, youll shape the technical roadmap for NLP and Speech at our company, identifying key opportunities to invest in foundational technologies and grow the team through strategic hiring and mentorship. Youll work cross-functionally with product, engineering, and design partners to ensure that advanced research translates into robust, scalable features that define the future of AI-assisted content creation.