Role Description As a Senior Machine Learning Engineer in Computer Vision, you will design and deliver advanced vision systems that power mission-critical applications for global and Fortune 500 companies. You’ll work across deep learning, large-scale data pipelines, and high-performance infrastructure, owning models end-to-end from experimentation to production deployment. This role is designed for engineers who think systems-level, understand the real-world constraints of ML at scale, and can turn ambiguous visual problems into high-impact, production-ready solutions. You’ll shape architectures, guide model strategy, and bring modern vision capabilities into enterprise environments where reliability, speed, and accuracy matter. Functional Responsibilities: - Develop and fine-tune models for tasks like image classification, object detection, segmentation, and generative modeling using TensorFlow, PyTorch, or Keras. - Implement techniques such as resizing, normalization, data augmentation, and feature extraction to improve model performance. - Optimize and deploy computer vision models on cloud platforms (AWS, GCP, Azure), edge devices, and specialized hardware (GPUs, TPUs). - Use CI/CD, model versioning, and monitoring tools to ensure reliable and scalable deployment of vision models. - Improve model speed and performance using quantization, pruning, and hardware acceleration techniques. Qualifications - +5 years of hands-on experience developing and deploying machine learning models in production environments. - Proven experience writing production-level code, with strong proficiency in Python. - Strong Python programming skills with proficiency in deep learning frameworks (TensorFlow, PyTorch, or Keras). - Expertise in designing, training, and fine-tuning models for: - Image classification (ResNet, EfficientNet) - Object detection (Faster R-CNN, YOLO, SSD) - Image segmentation (U-Net, Mask R-CNN) - Strong understanding of image preprocessing techniques (resizing, normalization, data augmentation). - Experience with computer vision libraries such as OpenCV and torchvision. - Experience with transfer learning and adapting pre-trained models. - Ability to deploy models on cloud platforms (AWS, GCP, Azure) and specialized hardware (GPUs, TPUs). - Familiarity with MLOps tools for automating ML pipelines. Benefits - Ownership through equity participation. - Annual company retreat. - Education bonus for continuous learning. - Company-wide winter break. - Paid time off. - Optional in-person events and meetups. - Tailored career roadmaps. - High-performance culture.

• Drive critical initiatives forward rapidly as part of an agile, embedded expert team • Deploy Principal-Vetted talent directly into partner technical teams • Participate in high-level engineering efforts to simplify cloud growth

Job Description About HiBob HiBob is a vibrant, fast-growing company on a mission to transform how modern, mid-sized companies manage their people. Our product serves over 5,300 customers globally, and our teams work in a true continuous delivery environment with modern microservices, automated QA, and frequent production deployments. About the Role We're looking for a hands-on Engineering Team Lead to join our Studio Team within the Platform Unit. This role combines people leadership, senior-level engineering across backend and frontend domains, and platform-oriented thinking, and plays a key part in building and scaling Bob's next-generation extensibility and AI-powered experience layer. As a Team Lead in the Studio team, you will lead a team of engineers while remaining actively involved in designing and implementing scalable systems that enable applications, widgets, workflows, and AI-driven experiences across the platform. If you're passionate about leading people, shaping technical direction, and staying hands-on while building zero-to-one platform capabilities and AI-native experiences - this role is for you. Why Join the Studio Team? Lead a team at the core of Bob's platform extensibility and future interaction model. Influence both user-facing experiences (applications, widgets, workflows) and the underlying platform and developer foundations. Work in a highly collaborative environment with strong Product, Platform, AI, and Design partners. Make a real impact at scale while growing as a technical and people leader. Job Requirements What You Bring Must Have - 7+ years of experience in software engineering with a strong backend or full-stack focus. - 3+ years of experience as an engineering team lead in a fast-paced environment. - Strong hands-on experience with modern backend technologies and system design. - Proven experience building and maintaining scalable distributed systems or platform capabilities. - Experience working with cloud platforms (AWS or equivalent). - Solid understanding of modern frontend technologies (e.g., React, component-based architecture). - Ability to balance technical depth, people leadership, and product/platform thinking. - Excellent communication skills in English (Hebrew is a plus). - Passion for both people management and hands-on engineering. Nice to Have - Experience building or operating AI / LLM-based systems in production. - Experience with extensibility platforms, APIs, or developer ecosystems. - Familiarity with workflow engines, orchestration systems, or event-driven architectures. - Background in developer experience (DevX), internal platforms, or shared services. - Experience with dynamic UI systems or design systems. - Experience mentoring engineers or leading internal guilds / tech forums. Job Responsibilities What You'll Do Technical Leadership & Hands-on Development - Lead the design, development, and operation of platform services and frameworks that power applications, widgets, workflows, and AI-driven experiences. - Take ownership of end-to-end delivery - from discovery and architecture through implementation, testing, deployment, and monitoring. - Address scalability, performance, and reliability challenges in systems enabling real-time, interactive, and AI-powered user experiences. Work closely with Platform, AI, Data, DevOps, Product, and Design teams to ensure seamless integration of Studio capabilities into the broader platform. Drive high engineering standards through code reviews, architecture discussions, testing practices, and automation. Team Leadership & Growth - Lead, mentor, and grow a team of engineers within the Studio team. - Own hiring, onboarding, coaching, and professional development of team members. - Foster a culture of ownership, collaboration, learning, and innovation. - Support engineers in growing their scope and taking end-to-end responsibility. Platform & Developer Experience - Contribute to and evolve Studio platform capabilities, including frameworks, SDKs, and tooling for building applications and workflows. - Improve developer and builder experience by enhancing extensibility, observability, CI/CD flows, and internal frameworks. - Enable and shape GenAI-powered experiences, including conversational interfaces, dynamic UI generation (GenUI), and data-driven workflows. - Collaborate with Architects and Platform leadership to align Studio with long-term platform and extensibility strategy. Benefits HiBob is a village filled with amazing people and we're especially proud of that. It's a place where Bobbers can be themselves. We're about fun, dreams, hopes and ambition, just as much as we are about precision, growth, and top performance. Becoming a Bobber means you'll receive competitive compensation, benefits, and pre-IPO equity alongside all of this: - Company share options plan - We have a flexible hybrid working model - Work from home allowance- to get your home office set up! - Payment for sick leave from the first day - 2 Social Impact days per year for volunteering - Annual Headspace subscription and wellness benefits - Awesome employee referral program- $2,500 for each successful referral with an additional ambassador programme - 10 bis or cibus/wolt- you get to pick! - Transportation allowance - Dog-friendly - Temporary remote work from anywhere in the world for up to 2 months (after 6 months of employment) - Fun company and team social events (locally and virtually with our global teams) - Bob balance days - 4 additional days within a calendar year - Enjoy a company-wide long weekend at the beginning of each quarter If this sounds like something you've been looking for, we'd love to have you. Come on, join our village!

Role Description We're looking for PhD or Master's students, and gifted undergrads to spend an internship with us working on building RL training environments for large language models. This role blends research and engineering. It will require you to both develop novel approaches and realize them in code. Your work will include: - Designing and implementing RL environments - Conducting experiments and evaluations - Delivering your work into production training runs - Collaborating with other researchers and engineers Qualifications - You're an undergrad or PhD student in CS, ML, math, physics, or a related field. - You write real code, not just research prototypes. - You read ML papers for fun in your free time. Requirements - Strong Python skills - Familiarity with how LLMs work, what they're good at, and where they fall short - Ability to work independently, take feedback, and iterate fast - You may be a good fit if one of the following applies: - You understand transformer internals and have worked with training or inference code - You've written CUDA kernels or worked with low-level GPU programming - You have a research area you know deeply (publications, public code, or strong coursework) - You read broadly across ML and can connect ideas from different subfields - You've built interactive environments, simulations, or complex software systems Benefits - Paid Internship with opportunity to return full time based on performance - Ownership and autonomy in a fast moving startup environment - Opportunity to work with top machine learning engineers - Competitive cash and equity compensation (>90th percentile) - Lunch provided everyday onsite - Weekly snack orders Company Description Preference Model is building automated ML research engineering. Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions. Our founding team has previous experience on Anthropic’s data team building data infrastructure, and datasets behind Claude. We are partnering with leading AI labs to push AI closer to achieving its transformative potential.