דרושים » תוכנה » Experienced Machine Learning Engineer

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're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of Machine Learning, GenAI, and computer vision within the automotive sector.
With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply Embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of UVeyes inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges.
A day in the life and how youll make an impact:
* Design and Development of novel, robust and efficient Machine Learning / Deep Learning algorithms for major Vision challenges.
* Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems.
* Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data -centric AI methodologies (active learning, data curation).
* Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for Real-Time inference constraints (on Edge/Cloud devices).

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 Senior ML Engineer
Responsibilities:
Work on our core data and machine learning infrastructure, which is at the heart of our 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.
Who You Are:
A problem solver at heart, you have a passion for excellence, you love to learn but know when its time to deliver and make ends meet. You arent threatened by a complex, dynamic and demanding environment. There is no I in team, is a motto you believe in deeply and you are always looking out for your peers. You know how to take ownership and drive projects to completion.

As a Machine Learning Engineer, Youll work with top notch engineers and machine learning scientists on bringing it to the next level and enabling optimal customer experience while having a significant impact on the business. The work will focus on data and ML foundations for reusable training, optimization and deploying causal machine learning models.



Key Job Responsibilities and Duties:

Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.

Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets for model features and data monitoring. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.

Building machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide personalized recommendations to users.

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.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

Come join the team as a Staff Machine Learning Engineer.
We are seeking a highly skilled ML engineer passionate about building a world-class platform at a high scale, specifically focused on delivering AI capabilities.
You will be part of a vibrant team of AI Scientists and ML Engineers, helping to build the next generation of awesome products and experiences using cutting-edge Generative AI technology.
If you love having stretch goals, challenges, and making customers incredibly happy while fostering your obsessive need for perfect code and user experience, this is the job for you.
Responsibilities:
Design, implement, and enhance services at large scale, specifically focusing on improving Generative AI inference, quantization, optimization, finetuning, and evaluation.
Use your coding expertise to design and implement scalable, modular, and secure services.
Develop backend systems that support serving of LLMs and AI Agents at scale, utilizing the latest industry tools and techniques.
Work cross-functionally with product managers, AI scientists, business units, and other engineers to understand, implement, refine, and design Generative AI models.
ng end-to-end responsibilities including technical documentation and automation tests.
Interact with a variety of data sources, working closely with peers to refine features from the underlying data and build end-to-end pipelines.
Resolve defects and bugs during testing, production, and post-release patches, and participate in peer code reviews.
Explore the state-of-the-art technologies and apply them to deliver customer benefits.

We are seeking a highly motivated and talented Junior AI Scientist to join our FILM (Foundation Intelligence & Learning Models) team. This role is designed for an early-career professional or a recent graduate who is passionate about driving customer impact, through the frontier of Artificial Intelligence, Generative AI and agentic architecture. As a Junior AI Scientist, you will work closely with senior researchers and engineers to develop, refine, and deploy cutting-edge AI solutions that impact our core technology stack.
Responsibilities:
Assist in the research and development of Generative AI (GenAI) applications and frameworks.
Clean, analyze, and interpret large datasets to derive actionable insights for model training and evaluation.
Participate in the full lifecycle of GenAI development, from initial concept to deployment and monitoring.
Stay up-to-date with the latest advancements in GenAI/ML research and propose innovative ideas to solve complex problems.

We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge

We are looking for a Senior AI Researcher to work closely with our delivery team, translating real-world clinical and scientific questions into rigorous AI and machine learning solutions. In this role, you will lead the development of methodologies, models, and benchmarking frameworks that address complex clinical problems using our unique immune-cell data. Your work will directly impact how our partners understand biology, evaluate hypotheses, and make decisions.

Location: Ramat Gan (hybrid model).

What will you do?
Partner with the collaborations team and scientists to frame complex clinical and biological questions as well-defined data science and modeling problems.
Design, implement, and evaluate the right analytical and modeling approaches for each problem, including robust benchmarking and validation strategies.
Clearly communicate results, limitations, and tradeoffs to internal teams and external partners, enabling confident, data-driven decisions.
Establish best practices for rigor, reproducibility, evaluation, and documentation across delivery-focused data science work.
Work hand-in-hand with immunologists, computational biologists, AI scientists, and engineers to ensure solutions are scientifically sound and production-aware.
Translate modeling solutions into engineered and iterable products used by the internal collaborations team.