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Location: EMEA; Romania; Ireland; Portugal; United Kingdom; Spain; Brazil; Poland; Canada ✨ ONE PLATFORM, A WHOLE WORLD OF OPPORTUNITY The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere. We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing: - Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time - Named one of America's Greatest Startup Workplaces 2026 https://www.oysterhr.com/library/oyster-2026-newsweek-award by Newsweek - A G2 Spring 2026 Leader https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026 across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance - The only B Corp-certified global employment platform ~ independently verified since 2023 Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one. And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply. Location: Fully remote. To create the best experience for you and to meet our business needs, this role requires you to be based within the EMEA or AMER regions. You’ll join Oyster as a Senior AI Solutions Engineer, reporting to the AI Director and partnering closely with functional leadership across Oyster. Your mandate goes beyond automating individual tasks. You’ll help make Oyster’s business functions AI native, initially across areas such as People & Legal, Finance, and Operations. This means rethinking how people work with AI, where agents can take on operational work, and where human judgement creates the most value to build a more effective AI enabled organization. You’ll be part of a connected group of Senior AI Solutions Engineers transforming different departments across Oyster. Together, you’ll establish shared standards, reuse successful approaches, and ensure Oyster’s AI transformation is coordinated rather than siloed. This is a senior, hands on role. You’ll independently identify high value opportunities, decide where AI should and should not be used, and lead complex solutions from discovery through adoption and measurable business impact. Successful candidates will be aligned to the business function where their experience, strengths, and interests can create the greatest impact, with the flexibility to support different functions as Oyster’s transformation priorities evolve.   CORE RESPONSIBILITIES Make business functions AI native Reimagine how teams work with AI. Move teams from manually operating tools and workflows toward humans orchestrating AI powered ways of working, with human judgement where it matters. Shape the AI roadmap Partner with functional leaders to identify, prioritize, and frame high impact transformation opportunities. Lead solutions from start to finish Own complex initiatives from an ambiguous problem through design, build, deployment, adoption, and improvement. Build best in class AI agents and solutions Design, build, test, and continuously improve reliable AI agents, agentic workflows, automations, and integrations using LLMs, orchestration platforms, APIs, tools, and enterprise data sources. Apply sound judgement Balance value, feasibility, risk, data quality, maintainability, and human oversight. Recognize when AI is not the right solution. Drive AI adoption and self sufficiency Partner with functional leaders, managers, and champions to embed AI into everyday work. Help teams move beyond consuming AI outputs toward confidently creating reusable prompts, workflows, and AI powered ways of working. Own solutions beyond launch Measure adoption, quality, reliability, and business impact after release. Continuously improve solutions based on real usage and outcomes rather than treating launch as completion. Connect the organization and raise capability Build trust with functional leadership, share reusable patterns with AI Solutions Engineers supporting other departments, mentor colleagues, and help teams develop the skills and confidence to operate effectively in an AI enabled environment.   MINIMUM REQUIREMENTS - 3+ years of hands on AI and automation experience, supported by broader experience delivering complex solutions in business operations, functional transformation, Solutions Engineering, systems integration, or a related field. - A track record of redesigning workflows or operating models, rather than only automating isolated tasks. - Experience independently leading complex, cross functional initiatives from an ambiguous problem to measurable business impact. - Strong automation capability using tools such as n8n, Zapier, Make, or comparable orchestration technologies. - Strong hands on experience designing, building, deploying, and improving production AI agents and agentic workflows using LLMs, APIs, tools, and enterprise data. - Strong experience in at least one complex business function such as People, Legal, Finance, Operations, or a related area. - Experience integrating business systems through APIs, webhooks, and authentication mechanisms. - Strong judgement about where AI can create value, where processes need deeper redesign, and where automation should not be used. - Ability to influence functional leaders, challenge assumptions constructively, and align technical and nontechnical stakeholders. - A track record of mentoring others, sharing expertise, and raising standards across a team.   BONUS EXPERIENCE - Experience with enterprise systems and platforms used across functions such as People, Legal, Finance, or Operations. - JavaScript, Python, or SQL experience. - Familiarity with RAG, MCP, AI evaluation, observability, governance, or security controls. HOW WE WORK TOGETHER AT OYSTER Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team. Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the Oyster Public HQ https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d so other global teams can learn from us. HOW YOU WORK With diverse locations, cultures, and needs, we created How YOU Work; https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395 a program supporting your whole human experience at Oyster: - Work from anywhere: Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere. - Paid time off: Enjoy 40 days off per year (including holidays and vacation), or more if required by your country. - Mental health support: Access Plumm https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7, our mental well-being service. - Wellbeing allowance: Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options. - Flexible parental leave: All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally. - WFH stipend: Receive a stipend for your laptop and home office equipment to get you set up quickly. ✨ THE BEST JOBS SHOULD BE AVAILABLE TO EVERYONE  We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment. Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email jobs@oysterhr.com with the subject line: Interview Accommodations. Our available positions are on our careers page. Our team will only contact you from an @oysterhr.com email, and we will never ask for money as part of an interview process or job offer. If you receive a suspicious email about Oyster jobs or are directed to a site other than www.oysterhr.com/careers http://www.oysterhr.com/careers, please report it via our Compliance and Ethics Helpline https://faceup.com/c/8tpzyyye.

Location: United Kingdom; Spain; Hungary; Bulgaria; Poland; Italy; Netherlands; France Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual team offsite: Each year, we bring your entire team together in a new location - past offsites have included Croatia, Italy and Cancún - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE We’re looking for an experienced Data Engineer to join our Data team. You will build and scale our data pipelines, establish best practices, ensure data quality, and enable self-service data access across teams. - Own and streamline data pipelines from ingestion to delivery, ensuring they are reliable, scalable, and efficient. - Implement and maintain dbt best practices, data standards, and quality controls. - Build self-service tooling and write clear documentation to empower cross-functional teams (Engineering, Revenue Operations, Growth, and others) to independently meet their data needs. - Create AI agents to serve data questions for others REQUIREMENTS Demonstrated experience formalising and scaling data pipelines, ideally as one of the first or early data engineers on a growing team. - Expert knowledge of dbt (required). - Proficiency with tools across the modern data stack (Python, SQL, BI tools). - Strong infra fundamentals (Terraform or other infrastructure as code, GCP or other cloud providers) - Structured thinking; ability to simplify complex, messy data into clear structures. - Strong ability to understand varied stakeholder requirements and build generalised solutions. LOCATION This role is remote and can be executed globally. If you prefer, you can work from our offices in London, Warsaw, New York. #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: Canada, Vancouver, BC Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a Senior Prototype Engineer to drive the development, assembly, integration, and validation of advanced humanoid robotic systems, with a particular focus on robotic hands, arms, end-effectors, and complex electromechanical mechanisms. This role combines deep hands-on engineering expertise with proven technical leadership and team management experience. You will take ownership of complex prototype development activities, guide engineering execution, and work closely with Mechanical, Electrical, Embedded Software, and Controls teams to transform innovative designs into reliable, high-performance robotic systems. We are looking for someone who has successfully led and developed technical teams, established efficient prototyping processes, and delivered complex hardware projects in fast-moving engineering environments. As our Vancouver robotics operations continue to grow, this position offers the opportunity to progress into a broader technical leadership role, helping shape our prototyping capabilities, engineering standards, and team development. Your work will directly influence the technical quality, development speed, and scalability of Humanoid's next-generation robotic platforms. WHAT MAKES THIS ROLE EXCITING - Take ownership of complex humanoid robot prototyping, including dexterous hands, arms, actuators, and advanced electromechanical assemblies. - Combine hands-on engineering with technical leadership, guiding complex prototype development from concept through validation. - Apply your previous team management and mentoring experience to strengthen engineering execution and build effective prototyping practices. - Solve challenging problems in robotic manipulation, precision actuation, sensor integration, and hardware-software interaction. - Collaborate with a multidisciplinary robotics team spanning mechanical, electrical, embedded software, and controls. - Play a key role in scaling Humanoid's prototyping capabilities, with potential to grow into a broader team leadership position. WHAT YOU’LL DO - Lead the development, assembly, integration, and commissioning of complex robotic prototypes, including hands, arms, end-effectors, actuators, sensors, and electromechanical subsystems. - Take ownership of prototype development from initial build through calibration, testing, debugging, validation, and design iteration. - Provide technical leadership and direction to engineers and technicians, helping establish priorities, resolve engineering challenges, and maintain execution quality. - Apply previous team management experience to mentor technical team members, develop capabilities, and establish effective engineering workflows. - Coordinate prototype development activities, ensuring clear technical priorities, efficient resource allocation, and alignment with engineering milestones. - Drive advanced hardware troubleshooting, root-cause analysis, and failure investigation across mechanical, electrical, and embedded systems. - Oversee the integration, calibration, and performance optimization of actuators, encoders, force/torque sensors, tactile sensors, and robotic control interfaces. - Partner with Mechanical, Electrical, Embedded Software, and Controls teams to identify design limitations, integration risks, and opportunities for performance improvement. - Lead and contribute to technical design reviews, providing practical engineering feedback on assembly, reliability, serviceability, and manufacturability. - Establish and improve prototype assembly procedures, integration workflows, testing methodologies, and validation standards. - Drive rapid prototyping and engineering iteration, ensuring timely resolution of technical blockers and efficient development cycles. - Support system-level testing, performance characterization, reliability assessments, and prototype-to-production transitions. - Develop and maintain technical documentation, including assembly instructions, test procedures, troubleshooting guides, SOPs, and engineering reports. - Collaborate with engineering and program leadership to plan prototype builds, track technical progress, manage risks, and communicate development priorities. - Work closely with teams across Vancouver, London, and Boston, supporting cross-site integration and technical collaboration. - Promote a safe, organized, and efficient prototyping environment, maintaining appropriate tools, equipment, and engineering practices. WE’RE LOOKING FOR - 10+ years of professional experience in robotics prototyping, mechatronics, electromechanical integration, or advanced robotic hardware development. - 5+ years of proven track record directing technician groups within a dynamic research and development setting. - Demonstrated experience mentoring, developing, and coordinating technical team members, with the ability to establish priorities and drive engineering execution. - Bachelor's or Master's degree in Robotics, Mechatronics, Mechanical Engineering, Electrical Engineering, or a related technical discipline, or equivalent practical engineering experience. - Strong hands-on experience building, integrating, testing, and troubleshooting complex robotic or electromechanical systems. - Proven track record of taking complex hardware prototypes from concept through integration, commissioning, validation, and delivery. - Deep understanding of precision mechanical assemblies, actuators, motors, sensors, wiring, and embedded hardware interfaces. - Experience with fine-pitch soldering, precision wiring, cable assemblies, connectors, and electrical integration. - Strong knowledge of actuator commissioning, sensor calibration, motor control interfaces, and robotic system testing. - Ability to interpret mechanical drawings, electrical schematics, wiring diagrams, and engineering documentation. - Experience using laboratory and diagnostic equipment, including oscilloscopes, multimeters, power supplies, and precision measurement instruments. - Demonstrated ability to lead complex troubleshooting, root-cause analysis, and engineering problem-solving activities. - Experience establishing or improving prototype assembly, integration, testing, and validation processes. - Strong project coordination skills, including technical planning, resource prioritization, risk management, and cross-functional execution. - Excellent communication skills, with the ability to collaborate effectively with engineering teams, technical leadership, and program stakeholders. - Ability to balance hands-on technical involvement with broader engineering leadership responsibilities in a fast-paced R&D environment. BONUS QUALIFICATIONS - Experience developing humanoid robots, dexterous robotic hands, robotic arms, or advanced manipulation systems. - Previous experience building, scaling, or managing a robotics prototyping, integration, or hardware development team. - Experience with multi-DoF robotic mechanisms, precision actuators, transmissions, and complex joint assemblies. - Experience with tactile sensors, force/torque sensors, encoders, IMUs, and robotic sensing technologies. - Knowledge of motor control systems, drive tuning, actuator performance analysis, EtherCAT, or CAN communication protocols. - Experience with rapid prototyping and fabrication, including FDM/SLA 3D printing, CNC machining, and laser cutting. - Familiarity with SolidWorks or similar CAD tools and the ability to perform mechanical design modifications. - Experience using Python, ROS/ROS2, or other tools for robotic hardware testing, calibration, or automation. - Experience developing automated test setups, hardware validation infrastructure, or data acquisition systems. - Experience supporting hardware NPI, prototype-to-production transitions, or low-volume robotic manufacturing. - Background in robotics, autonomous systems, aerospace, automotive, or advanced hardware startups. WHAT WE OFFER - Comprehensive extended health benefits starting on your first day, including fully paid medical and dental, virtual care, employee and family assistance, and worldwide emergency medical support. - Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. - Paid end-of-year shutdown: annual company-wide holiday closure spanning Christmas through New Year’s Day. - Competitive equity: stock options with meaningful upside as we scale. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.

• Design and build an in-house position-keeping system (from architecture to integration). • Calculate market, credit, and liquidity risk across FX, derivatives, FI, and treasury.

-погружаться в процессы, данные и бизнес-логику клиентского подразделения. -общаться с заказчиками и пользователями, уточнять потребности и формулировать техническое решение.

Location: Multiple Countries Nitka Technologies develops software for customers in the US and Europe and brings together about 300 professionals from Eastern Europe, North and South America, Armenia, Georgia and Kazakhstan. We are looking for an experienced DBA (Databricks) for a long-term project. The customer is a company in California, an industry leader in the sale of tickets to events in Europe and the USA. We offer 100%  remote, full-time work. Main tasks: Manage multiple Databricks workspaces (dev/qa/prod); Configure cluster policies, governance & compliance; Create & maintain unity catalog objects: catalogs, schemas, grants, service principals, external storage etc; Monitor and debug failed / long-running jobs using system tables (job_run_timeline, node_timeline, workflow_run); Troubleshoot cluster crashes, driver OOM, executor failures, memory leaks; Investigate Python / Spark errors, dependency conflicts (PyPI, WHL, Maven) Assist users with cluster/job configuration, notebook errors, unity catalog permissions; Explain platform limitations and best practices to Data engineers; Maintain confluence pages with platform rules & troubleshooting guides; Requirements: Experience in implementation, integration or technical support; Experience with Linux, Bash; Confident SQL skills; Strong experience of working with AWS Infrastructure (ec2, s3, iam, vpc, secret management, sqs); Experience with Python sufficient for writing small scripts or applications; Experience of maintaining Databricks jobs & environments; Experience with REST API/SDK; Understanding of file-based databases (DeltaLake, Parquet, Hive); Understanding of of cluster types & node families; Spoken English at Intermediate level or higher; Would be a plus: Databricks REST API / Databricks SDK; Working with schema evolution, time travel, vacuum, compaction, z-order; Debugging corrupted delta tables (conflicting commits, tombstones, missing checkpoints); Understanding of acid implementation on top of object storage; Spark knowledge (jobs, partitions, queries), experience in Kafka or similar technology, familiarity with Terraform / Gitlab CI; Cost monitoring for platform services and objects; Experience in enterprise Data platforms; Working conditions: Nearshore candidates preferred, with availability to work EST or Pacific Time hours Remote work with no time trackers, flexible working hours Full-time (8 hours/day) Attractive USD compensation Paid vacation, holidays, sick leaves

Location: Multiple Countries Nitka Technologies develops software for customers in the US and Europe and brings together about 300 professionals from Eastern Europe, North and South America, Armenia, Georgia and Kazakhstan. We are looking for an experienced Platform Administrator (Databricks) for a long-term project. The customer is a company in California, an industry leader in the sale of tickets to events in Europe and the USA. We offer 100%  remote, full-time work. Main tasks: Manage multiple Databricks workspaces (dev/qa/prod); Configure cluster policies, governance & compliance; Create & maintain unity catalog objects: catalogs, schemas, grants, service principals, external storage etc; Monitor and debug failed / long-running jobs using system tables (job_run_timeline, node_timeline, workflow_run); Troubleshoot cluster crashes, driver OOM, executor failures, memory leaks; Investigate Python / Spark errors, dependency conflicts (PyPI, WHL, Maven) Assist users with cluster/job configuration, notebook errors, unity catalog permissions; Explain platform limitations and best practices to Data engineers; Maintain confluence pages with platform rules & troubleshooting guides; Requirements: Experience in implementation, integration or technical support; Experience with Linux, Bash; Confident SQL skills; Strong experience of working with AWS Infrastructure (ec2, s3, iam, vpc, secret management, sqs); Experience with Python sufficient for writing small scripts or applications; Experience of maintaining Databricks jobs & environments; Experience with REST API/SDK; Understanding of file-based databases (DeltaLake, Parquet, Hive); Understanding of of cluster types & node families; Spoken English at Intermediate level or higher; Would be a plus: Databricks REST API / Databricks SDK; Working with schema evolution, time travel, vacuum, compaction, z-order; Debugging corrupted delta tables (conflicting commits, tombstones, missing checkpoints); Understanding of acid implementation on top of object storage; Spark knowledge (jobs, partitions, queries), experience in Kafka or similar technology, familiarity with Terraform / Gitlab CI; Cost monitoring for platform services and objects; Experience in enterprise Data platforms; Working conditions: Remote work with no time trackers, flexible working hours Full-time (8 hours/day) Attractive USD compensation Paid vacation, holidays, sick leaves

Location: Islamabad, Pakistan Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer , who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential. Key Responsibilities Develop, deploy, and maintain machine learning models and systems Conduct in-depth data analysis, preparation, and processing Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing Follow established security guidelines and identify potential risks Collaborate with peers to review and ensure designs are effective, flexible, and reusable Solve issues and provide feedback for engineering design and delivery processes Ensure that features are deployed according to requirements and operate without unintended side effects Create and maintain comprehensive documentation for models and processes Monitor and support deployed solutions to ensure they meet performance expectations Actively seek out information and internal solutions to ensure reusability and adoption of common technologies Our expectations 3+ years of experience in the Field. Previous software engineering experience is preferrable Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data). Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics. Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle. Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes. The ability to design solutions using common design patterns and various design tools. Experience in experiment design and the ability to validate the credibility of information from various sources. A solid understanding of the business value of delivered features. Strong problem-solving skills, with an emphasis on using technical facts and reasoning. Excellent communication and collaboration skills, including active listening and the ability to build consensus. A strong drive for continuous self-development and a collaborative mindset for contributing to communities. Ability to balance quality and speed depending on the case, and justify your decision Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers English communication skills Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Senior Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Help us challenge injustice by creating fair choices for millions of people across in 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary starting from 59 200 EUR gross Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid The Freight vertical provides essential logistics solutions for Private and SMB clients. This role covers the EMEA & APAC regions, with a strong operational focus on Kazakhstan as well as broader EMEA and APAC expansion . The key purpose of this role is to own and drive the development and scalable growth of the Freight business. As a Business Development Manager, you will be responsible for end-to-end business expansion — including commercial performance, pricing and unit economics, analytics, go-to-market strategy, and cross-functional execution. You will validate and scale growth hypotheses, ensure sustainable GMV and revenue growth, and build repeatable business models across your target markets. Key Responsibilities Own business growth and expansion of the Freight vertical across Kazakhstan, EMEA, and APAC, including revenue, GMV quality, and unit economics. Develop and manage pricing and tariff models, ensuring sustainable margins and competitive positioning. Own unit economics calculations and continuously optimize business performance. Drive analytical deep dives into business funnels (supply, demand, conversion, retention) and identify growth opportunities. Generate, validate, and scale business, product, marketing, and operational hypotheses in cross-functional teams. Own go-to-market initiatives, including branding, positioning, and collaboration with Marketing teams. Define and develop CRM logic: segmentation, lifecycle management, retention, and reactivation mechanics. Coordinate antifraud initiatives with risk and antifraud teams to ensure healthy marketplace economics. Conduct market and competitor analysis and contribute to long-term Freight vertical strategy. Own P&L for the region / vertical: planning, monitoring, and optimization of core metrics. Lead BD team and manage cross-functional stakeholders (Product, Marketing, Operations, Risk) to deliver business results. Qualifications 3+ years of experience in business development, commercial operations, or growth management in a marketplace or logistics/freight business. Advanced Excel / Google Sheets skills (financial models, unit economics, P&L modeling, tariff design, cohort analysis). Strong track record in funnel analysis, hypothesis testing, customer development (CustDev), and KPI monitoring. Direct experience with pricing, tariff modeling, CRM systems, and customer lifecycle management. Ability to independently analyze complex data, challenge assumptions with logic, and translate high-level strategy into clear execution frameworks. Strong execution and delivery mindset with the ability to work autonomously, decompose complex problems, and focus on high-impact initiatives. Excellent leadership and cross-functional stakeholder management skills. High level of empathy, resilience, and a constructive, low-toxicity approach to teamwork. Knowledge of SQL, Python, or A/B testing frameworks is a plus. Fluent English. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid We are looking for a Passenger Incentives Economics Manager to join our Marketplace Efficiency team and own the day-to-day operations of passenger incentives across inDrive markets. You will manage incentive budgets, operate and optimize discount and reward mechanics, analyze their impact on passenger growth and marketplace economics, and work closely with Analytics, Tech, Finance and Marketinh teams to make incentive management increasingly data-driven and automated. This is a hands-on role with a direct impact on the passenger side of the marketplace, offering the opportunity to work across multiple countries and emerging markets and influence how incentives are designed, allocated and scaled. Key Responsibilities Manage the weekly passenger incentives budget across countries and incentive mechanics, ensuring effective budget allocation and pacing. Operate and optimize the portfolio of passenger discounts, rewards and other monetary incentive mechanics based on business objectives and performance. Monitor incentive performance using data and dashboards, analyze uplift, incrementality, CPAR and net revenue impact, and identify opportunities to stop, scale or adjust initiatives. Work with Analytics and Tech to develop and improve tools, models, monitoring and automation for incentive management and budget allocation. Translate business needs into clear requirements and drive their implementation with analysts, engineers and product teams. Prepare regular performance insights and recommendations based on data. Continuously improve operational processes and move incentive management from manual decisions towards automated, algorithm-driven solutions. Skills, Knowledge & Expertise Degree in Economics, Finance, Business, or a closely related field is required. 3+ years of experience in operations, revenue management, growth, strategy, analytics or consulting. Hands-on experience with pricing, incentives, promotions or revenue management — including setting up initiatives, testing them and measuring their impact. Strong analytical skills and experience working with large datasets; advanced Excel skills. Solid understanding of unit economics, incrementality and A/B testing, including the use of control groups to measure the true impact of incentives. Understanding of marketplace dynamics and how passenger-side incentives can affect supply, demand and the driver side of the marketplace. Experience translating business needs into requirements for Product, Analytics or Tech teams and driving initiatives through to delivery. Strong ownership and execution skills, with the ability to structure ambiguous problems and make data-driven decisions. Strong stakeholder management and communication skills. Fluency in English. Would be a plus: Experience working across multiple countries or regions. SQL, Python or experience with BI tools such as Tableau or Power BI. Experience with loyalty, cashback or points-based products. Experience working with ML-driven targeting or recommendation systems. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary starting from 64 700 EUR Gross. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context. This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks. Key Responsibilities Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact Keep models healthy after launch as data and cities shift Skills, Knowledge and Expertise Minimum qualifications 5 or more years building models that shipped and improved a production metric Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers Experience taking a model to production and owning it afterwards The ability to work across teams, since search quality work generates data and engineering tasks that others own Preferred qualifications Depth in geocoding, autocomplete, or place search Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes Relevance tuning on OpenSearch or Elasticsearch, including analyzers Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Limassol, Cyprus Workplace: hybrid Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own search and recommendation stack, which means we own the data, the ranking, and the measurement. The team is cross-functional, spanning backend, machine learning, mobile, and QA, and works with a product manager focused on relevance and with geo analysts. It owns place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, and its own search screens on Android and iOS. It is measured on order conversion, search conversion, and mean reciprocal rank We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context. This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks. Key Responsibilities Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact Keep models healthy after launch as data and cities shift Skills, Knowledge and Expertise Minimum qualifications 5 or more years building models that shipped and improved a production metric Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers Experience taking a model to production and owning it afterwards The ability to work across teams, since search quality work generates data and engineering tasks that others own Preferred qualifications Depth in geocoding, autocomplete, or place search Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes Relevance tuning on OpenSearch or Elasticsearch, including analyzers Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Annual salary from 70 700 EUR gross Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid The AI Solution Delivery team is expanding its capabilities in NLP to build production-grade AI products. We are looking for a Senior Data Scientist to architect, build and deploy complex models for automating customer support operations. You will be responsible for selecting the right technical approaches and ensuring the scalability of our solutions. A proven track record in applying advanced NLP techniques to real-world problems is required. Key Responsibilities Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance Translate complex business goals into well defined data science problems and quantifiable metrics Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance Support the development and growth of other team members through mentorship and participation in onboarding programs Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact Communicate complex technical concepts and findings clearly and concisely to both technical and non technical stakeholders Skills, Knowledge and Expertise 5 years of professional experience in a data science or machine learning role with deep focus on NLP. Previous software engineering experience is preferrable. An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus Expert level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit learn). Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields. Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment. Proven experience with event systems, deployment environments, and maintaining production services. Familiarity with technologies for streaming, batch, and async data processing. Strong understanding of software system design principles and the ability to contribute to architectural discussions. Experience in experimental design to validate hypotheses and measure the effectiveness of solutions. A solid grasp of security, risk, and control concepts in a production environment. Conditions & Benefits Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.