דרושים » תוכנה » Machine Learning Engineer

We are seeking a highly skilled and motivated Engineering Tech Lead to join our Data Science Engineering team. The ideal candidate will have a deep understanding of software development and the ability to guide technical solutions.
This role requires a combination of technical expertise, strong problem-solving skills, and the ability to collaborate effectively with cross-functional teams. As an Engineering Tech Lead, you will play a crucial role in exploring and investigating solutions and technologies, contributing to technological and architectural decisions with a hands-on approach.
Key Responsibilities:
Develop and maintain software infrastructure and solutions to support the efficient development, deployment, and maintenance of machine learning models and our surveillance pipe solution in production.
Collaborate with data scientists, engineers, and subject matter experts to deliver high-quality, production-ready machine learning models and a fully integrated scalable solution.
Design and implement software architecture for machine learning solutions.
Work with containerized environments such as Kubernetes and Docker.
Utilize AWS for cloud-based machine learning solutions.
Conduct unit testing and ensure continuous integration and continuous deployment (CI/CD) practices are followed.
Work in a production environment and closely with data science teams to ensure seamless model deployment and maintenance.
Stay updated with the latest advancements in machine learning, software development, and related technologies.

Youll work in an exciting environment alongside some of the most innovative people in the industry, using cutting-edge tools and technologies. you have the opportunity to directly influence the products and solutions used by our clients worldwide, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN and thats just the beginning of what we have to offer! Join us and be a part of the best tech team as we Fuel The Fandom.

We are seeking a Machine Learning Engineer with a passion for developing production-grade software services and solving intriguing problems using Large Language Models (LLMs), data, and creative thinking. Join us in creating our next-generation automatic sports video content engine. If youre enthusiastic about cutting-edge NLP and Generative AI development, we want you!

As a Machine Learning Engineer, youll tackle complex business challenges using state-of-the-art NLP models in areas such as text generation, text classification, question answering, information retrieval, and more. You will collaborate closely with engineers, scientists, and product managers to make our language platform the best in its class.

What youll do:
Design and develop the engineering infrastructure to support all ML-related activities.
Work closely with Data Scientists and other stakeholders to define the ML system requirements for experimentation and production.
Define internal quality processes in the team, including code reviews, testing methodologies, and deployment processes.
Work on various tasks: architecture and design, coding, monitoring, working with cloud services, and working closely with MLOps.
Continuously explore new tools and practices in the ML and cloud processing world that can be harnessed for our mission to build a smooth ML development and serving pipeline.
Identify improvement opportunities, such as automating manual processes and cost-reduction opportunities.

Youll work in an exciting environment alongside some of the most innovative people in the industry, using cutting-edge tools and technologies. you have the opportunity to directly influence the products and solutions used by our clients worldwide, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN and thats just the beginning of what we have to offer! Join us and be a part of the best tech team as we Fuel The Fandom.

As an NLP team lead, you will solve hard business problems using SOTA NLP models, in the realm of text generation, text classification, question answering, information retrieval and more. You will pretrain, fine-tune and deliver to production large language models (LLMs), in multiple languages, and use your knowledge and creativity to answer business problems using real data. Youll also work with the Product team to shape our product roadmap, and contribute to brainstorming sessions on NLP projects.

What youll do:
Lead a team of exceptional NLP researchers.
Teach, mentor, and counsel the team, supporting their growth and professional development
Initiate, plan, prioritize, and manage ML projects, solving a real business problem for the largest sports organizations.
Translate business challenges into ML projects, brainstorm to identify optimal approaches, and conduct hands-on research to integrate data, product insights, and algorithms, generating business value.
Supervise production deployment, monitoring, and continuous learning of NLP models to ensure their optimal performance and adaptability.
Continuously evolve and help others evolve professionally, through joint work and mentoring, contributing to weekly brainstorming sessions, and staying up-to-date with the latest ML developments
Collaborate closely with Product and BizDev teams to align NLP initiatives with business objectives and product strategies.

As a DevOps Engineer, you will join our data & engineering team and design and manage scalable, cloud-based infrastructure focused on big data and machine learning. You will ensure high-scale production environments are reliable, secure, and efficient, supporting seamless ML/AI deployments.

What will you do?

Design, build, and maintain scalable and reliable infrastructure for our big data applications
Automate the deployment and scaling of our applications using Kubernetes and related technologies
Implement and maintain security and compliance protocols
Monitor and troubleshoot infrastructure and applications
Collaborate with product teams to define and implement infrastructure requirements
Stay up-to-date with the latest industry trends and technologies
Manage and optimize large GPU clusters

R-241031

We are seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities.

We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability.

Role & Responsibilities:
Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems.
Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments.
Build and maintain infrastructure for efficient model deployment, monitoring, and versioning.
Ensure high availability, performance, and security of backend services.
Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes.
Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems.

We are seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities.

We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability.

Role & Responsibilities:
- Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems.
- Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments.
- Build and maintain infrastructure for efficient model deployment, monitoring, and versioning.
- Ensure high availability, performance, and security of backend services.
- Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes.
- Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems.

We are looking for a Senior ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.

This role is designed for a senior technical leader who may focus on hands-on technical innovation or combine this with team leadership, depending on experience and career goals.

As Deep Learning Lead, you will take ownership of developing advanced single-cell representation models, driving our mission to create the world's leading foundation model of the immune system.

This role places you at the forefront of deep learning innovation, tackling complex challenges in modeling multimodal and time-series data from hundreds of millions of cells. You will design and refine transformer-based architectures and pre-trained foundation models to integrate diverse, high-dimensional datasets, unlocking insights for drug development and clinical trials.

You will lead the full model development lifecycle, from research and experimentation to scalable, production-ready deployment. Collaborating with a multidisciplinary team of experts, you will shape the technical roadmap, mentor team members, and foster a culture of innovation and excellence. This role offers a unique opportunity to develop cutting edge models tailored for the unique domain and make an impact on the pharma development domain bringing new drugs faster to the bedside.

Location: Ramat Gan, Israel (hybrid role)

What will you do?

Spearhead the architectural design and implementation of cutting-edge transformer models, pushing the boundaries of performance and efficiency
Lead and mentor a team of ML researchers and engineers, fostering a collaborative and innovative environment
Collaborate closely with cross-functional teams, including data scientists, product managers, and software engineers, to deliver impactful solutions
Contribute to the development of best practices and standards for transformer model development and deployment

We are looking for a Principal ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.

Youll work in an exciting environment alongside some of the most innovative people in the industry, using cutting-edge tools and technologies. you have the opportunity to directly influence the products and solutions used by our clients worldwide, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN and thats just the beginning of what we have to offer! Join us and be a part of the best tech team as we Fuel The Fandom.

We are looking for a Senior GenAI/NLP Algorithm Developer to join us in research and development of our next-generation automatic sports video content engine. If you are passionate about state-of-the-art NLP and Generative AI research we are looking for you!

What youll do:

The teams main focus: NLP & Generative AI.
Research and develop end-to-end real-time solutions for sports content automation using state of the art deep learning algorithms for text, speech, audio and data analysis.
Full R&D cycle, from problem definition and research to implementation and productization with a high level of autonomy.
In addition, part of the role & responsibilities will be:
Design, develop and implement state-of-the-art Generative models, prompt engineering and classical ML/NLP techniques to create high-quality solutions for demanding product-oriented NLP tasks.
Engage in collaboration with product, account, and customer success teams to establish success criteria and convert them into measurable objectives and quantitative measures.
Conduct training and evaluation of models within practical production scenarios.