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Location: United Kingdom (Hybrid); United Kingdom (Remote); Spain; Netherlands Workplace: Hybrid Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 Meet the team 👥 Here at Cleo, we have ~45 ML engineers ✨ They are the builders behind the AI that powers our product. They design experiments, create models that personalise financial insights, deploy fraud detection systems and scale our conversational AI, making sure that what we build genuinely helps people feel better about their money. From shaping product features and building the models that personalise our users' money journeys, to tackling fraud, scaling our systems and giving leaders the insights they need, our data team is at the heart of it all. About the role ✍️ We're hiring an Tech Lead ML Manager to join the existing data science function at Cleo. You’ll be working on models that support our understanding of a user’s financial life, building our foundational capabilities upon which all our product innovation depends, from the chat based Financial Assistant to our credit products. You’ll take on technical leadership and ownership of a workstream within the Financial Understanding pillar. We work at the intersection of LLMs and classical machine learning, trying to bring the advanced capabilities that are now possible at the speed and scale necessary for the size of Cleo’s userbase. - Leading and managing a team of circa. 4 MLE’s - Deploying machine learning models into production - Collaborating with product managers, backend engineers and analysts to play an active role in the planning and sequencing of work for the squad. - Helping define the roadmap for the squad/workstream What we're looking for 🕵 - At least 5 years of experience in data science, ML engineering or related roles - At least 1 year of management experience, ideally of a small team. - Ability to write production quality python code. - Experience deploying machine learning models into production - Experience with both LLMs and classical machine learning - Comfortable with complexity & developing a holistic understanding of a system in order to propose & build solutions WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Location: United Kingdom, London Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: We are seeking a Senior Director to lead our Enterprise Reporting and Analytics Engineering organization, a team of analytics engineers, report developers, visualization specialists, and people leaders. This organization focuses on the last mile of the enterprise data supply chain: the semantic models, curated data products, metric definitions, and consumption experiences that turn engineered data into decisions. This is not a traditional reporting leadership role; the classic notion of “reporting” in the form of a myriad of dashboards and filters is racing towards obsolescence. But the need for data and insights, and the need to deliver it in a way that is digestible and actionable, is timeless. Yes, governed dashboards and trusted reporting remain the foundation, and this leader must be excellent at that foundation. But the mandate is to move the organization decisively beyond static reporting toward a proactive, intelligent analytics capability: partnering with Data Science to productize and visualize their models, enabling generative AI and LLM-based access to our data, building exception-based systems that alert users when outcomes deviate from expectation in a statistically meaningful way, and designing agents that monitor data continuously and deliver insight without being asked. Analytics engineering shares much of its DNA with data engineering — modeling, transformation, testing, version control, CI/CD, performance and cost discipline — but is oriented toward business enablement rather than platform and pipeline. Success in this role therefore depends as much on partnership as on technical depth. This leader will work shoulder to shoulder with Data Engineering on the boundary between platform and consumption, with Product Management on roadmap and requirements, with Data Science on advanced analytic products, and with Analytics Operations on a disciplined intake and prioritization process that makes the best possible use of finite capacity. The ideal candidate has spent years building the traditional foundations — governance, metadata, lineage, dimensional modeling, engaging with enterprise BI platforms— and is now looking to apply that rigor to a fundamentally different generation of analytic products in new and innovative ways. What you'll be doing: Organizational Leadership Lead, coach, and develop an organization of approximately 30 people, including managing through frontline managers; own hiring, role clarity, career pathing, performance management, and succession planning. Define a multi-year vision and roadmap for enterprise reporting and analytics engineering, and translate it into quarterly outcomes the team and its partners can measure. Partner closely with Product Management to jointly shape the multi-year enterprise end-to-end data strategy. Own the organization's budget, vendor relationships, and contractor or offshore capacity. Establish and sustain an engineering culture within an analytics function: peer review, automated testing, documentation standards, source control, CI/CD, etc. Analytics Engineering and Data Architecture Drive maturity of the last-mile architecture in partnership with Data Engineering: curated marts, semantic layers, reusable data products, and certified datasets that serve reporting, ai enablement, data science, and downstream applications. Define and enforce dimensional modeling standards, transformation frameworks, and modular, tested, version-controlled analytics code. Own the enterprise metric layer so that key business measures carry a single, governed definition regardless of where they are consumed. Partner with Data Engineering to define clear contracts and handoffs between pipeline and platform work and last-mile modeling, including shared tooling, standards, and escalation paths. Manage query performance, warehouse consumption, and platform cost as first-class engineering concerns. Data Governance, Metadata, and Lineage Own cataloging, business glossary, data certification, and stewardship workflows, leveraging tools such as Atlan as the primary metadata platform. Maintain column-level lineage across the analytics estate to support impact analysis, change management, audit, and root-cause investigation. Leverage data access provisioning and entitlement models, including row- and column-level security, in partnership with Security, Privacy, and Compliance. Collaborate with Data Engineering to drive data quality monitoring, freshness and availability SLAs, observability, and incident response for analytic assets. Enterprise Reporting and Data Visualization Drive analytics engagement by leveraging enterprise visualization and provisioning platforms, including Domo and Tableau, in partnership with Data Engineering. Ensure best practices are followed in data architecture, governance, adoption, performance, and total cost management. Set visualization and information design standards that make reports readable, consistent, accessible, and decision-oriented. Rationalize the existing reporting portfolio: retire redundant and unused assets, consolidate overlapping content, drive down tech debt and drive consumption toward certified sources. Build a durable self-service capability through training, templates, community, office hours, and clear guardrails on what belongs in self-service versus centrally managed content. Advanced, Proactive, and AI-Enabled Analytics Partner with Data Science to productize their work: build the visualization, interaction, monitoring, and feedback loops that turn models and research into products the business actually uses. Partner with Product Management and Data Engineering to enable generative AI and LLM access to enterprise data. This includes preparing the semantic and metadata foundation that makes data legible to models, delivering conversational analytics, text-to-SQL, and retrieval-augmented experiences on governed sources, and establishing guardrails, evaluation, and accuracy monitoring so that answers can be trusted. Build exception-based analytics that detect when an outcome deviates from its expected value in a statistically significant way, using seasonality-aware baselines, forecast residuals, control limits, and anomaly detection rather than static thresholds. Route those exceptions to accountable owners with context, likely drivers, and a recommended next action; actively tune sensitivity and volume to prevent alert fatigue and preserve signal. Design and deploy analytic agents that proactively monitor data, investigate variances, assemble narrative explanations, and deliver insight into the tools where people already work. Shift the organization's consumption model from pull to push: the measure of success is not how many people opened a dashboard, but whether the right person was told the right thing at the right time. Cross-Functional Partnership, Intake, and Prioritization Operate as a true partner to Product Management: contribute to roadmap, requirements, user research, and release planning, and run analytics with a product mindset covering personas, adoption metrics, and asset lifecycle management. Partner with Analytics Operations to run a transparent intake, triage, sizing, and prioritization process, with published capacity, explicit tradeoffs, and reliable delivery commitments. Make capacity constraints visible to stakeholders and executives, drive reuse over one-off builds, and decline or defer work with evidence rather than friction. Serve as a senior, executive-facing partner to business functions, translating ambiguous business questions into well-scoped analytic solutions. What we're looking for: Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, Mathematics, Economics, or a related quantitative field; equivalent professional experience will be considered. 15+ years of progressive experience in data, analytics, or business intelligence, including 8+ years leading teams and 4+ years managing managers. Demonstrated experience leading an organization of 25 or more people in a large, matrixed enterprise. Strong hands-on foundation in SQL, dimensional modeling, and ELT/ETL design, with production experience on a modern cloud data warehouse or lakehouse (for example Snowflake, Databricks, BigQuery, Redshift, or Synapse) and a transformation framework such as dbt. Experience applying software engineering practices to analytics work, including Git-based workflows, automated testing, and CI/CD. Enterprise-scale leveraging of BI and data visualization platforms such as Domo, Tableau, Power BI, or Looker, including governance, provisioning, adoption, and cost management. Demonstrated ability to participate in driving data governance program covering catalog, lineage, glossary, stewardship, quality, and access, using platforms such as Atlan, Collibra, Alation, or Informatica. Proven track record of delivering jointly with Data Engineering and Product Management, with clear ownership boundaries and shared accountability. Direct experience partnering with Data Science, including operationalizing, visualizing, and monitoring model output for business consumption. Working command of the statistical concepts underlying exception detection, including hypothesis testing, confidence intervals, variance and control limits, seasonality, and forecasting. Experience running a formal intake, prioritization, and capacity planning process for a shared services or platform organization. Excellent executive communication and influence skills, with the ability to operate effectively amid ambiguity and competing priorities. Experience managing budget, vendor contracts, and platform licensing. Preferred Skills: Master's degree or MBA in a related field. Production experience delivering LLM-based analytics: retrieval-augmented generation over governed data, text-to-SQL or conversational BI, semantic layers designed for model consumption, and prompt, evaluation, and cost monitoring frameworks. Experience designing agentic workflows and orchestration for monitoring, investigation, and notification use cases. Hands-on experience with Atlan, Domo, and Tableau specifically. Proficiency in Python or R for prototyping, and familiarity with common statistical and ML libraries and MLOps concepts. Experience deploying anomaly detection at scale, including alert routing, suppression, and fatigue management. Familiarity with data product and data mesh operating models, domain-aligned ownership, and data contracts. Experience operating in an Agile or product operating model at scale, including portfolio, OKR, and roadmap management. Deep experience with the “Silicon Valley” school of Product Management, as exemplified by the “Marty Kagan”-style academic approach a significant plus. Experience leading global or matrixed teams, including offshore or vendor-partnered delivery models. Track record leading a major platform migration, consolidation, or reporting rationalization effort. Demonstrated success attracting, developing, and retaining senior technical talent in a competitive market. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Canada Role overview: We are seeking a GNC System Engineer for design, integration, verification, and operational support of GNC subsystems for our current and next-generation remote sensing and communications satellites. The role will require to design the complete subsystem, from algorithm development through hardware implementation, verification, and on‑orbit operation support. The role requires deep expertise in orbital dynamics, attitude‑determination & control, plus real‑time FSW definition and integration, and will work closely with subsystem and mission operations teams throughout the satellite life-cycle. Tasks summary: Architecture Concept & Requirements • Derive GNC functional, performance, and safety requirements (pointing accuracy, slew rate, orbit‑maintenance ΔV, fault‑tolerance) from mission level requirements. • Produce System Requirements, Interface Control document (ICD), and Description Document. • Perform requirement management and maintain bidirectional traceability throughout the project lifecycle. Modelling & Trade‑Study • Conduct trade studies on sensor suites and actuator families. • Perform high‑fidelity dynamics simulations (Matlab/Simulink, STK) to meet pointing requirements, maintain error budgets, control‑law stability, fuel consumption, and survivability margins. Algorithm Development • Design and implement attitude‑determination algorithms and orbit‑determination solutions. • Develop control laws for 3‑axis stabilization, slew maneuvers, station keeping algorithms • Validate algorithms with Monte‑Carlo analysis, worst‑case scenarios, and support SIL/HIL testing on avionic test bench. Cross‑Functional Coordination, Stakeholder & Program Interaction • Translate algorithms into FSW requirements running on real‑time operating systems. • Collaborate with the C&DH and FSW teams to implement TM/TC, schedulers and FDIR logic for GNC. • Present technical status, risk analyses, and trade‑study results to senior management. • Negotiate and maintain ICDs with subsystems. • Support B&P (Phase 0 & pre-phase A). Hardware Selection & Design • Specify sensor and actuator hardware, perform interface definition (electrical, mechanical, thermal) and conduct trade on redundancy architectures. • Work with structures and thermal engineers to ensure proper mounting, thermal paths, and vibration survivability of GNC hardware aligning with payload requirements. • Review harness routing and power distribution for GNC electronics. Integration & Verification (IVV) • Author Verification Plans, Test Matrices, and Validation Procedures for unit, subsystem, and spacecraft level GNC tests. • Lead functional tests: sensor calibration, actuator command‑response, closed‑loop attitude‑control on testbeds, and on‑orbit checkout sequences. • Conduct failure mode and effects analysis (FMEA), fault tree analysis (FTA), and reliability prediction. Technical Leadership & Mentorship • Mentor, guide junior engineers and interns. • Act as technical liaison with customers, partners and external vendors • Act as Continuous Improvement stakeholder • Contribute to Client’s knowledge‑base, process enhancements, and standards. Configuration, Documentation & Standards Management • Maintain GNC standards (sensor/actuator interface, filter design, control‑law documentation). • Ensure all artefacts, analysis, software, deliverables and documentations are version controlled in PLM environment. • Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). • Support Technology Road‑Mapping & Innovation On‑Orbit & Operations Support • Support procedure developments (detumble, orbit‑maintenance, safe‑mode…etc.). • Provide real‑time GNC support during launch, early‑orbit checkout, and contingency events. • Analyse on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications: • B.Sc. in Electrical Engineering, Aerospace or Physics, (M.Sc. preferred), focused on flight dynamics, control theory, or navigation with 10+ of GNC/AOCS experience on LEO/MEO/GEO platforms. • Orbital mechanics, attitude dynamics, and control-law design (classical and modern optimal control). • Proficiency with navigation sensors and actuators. • Experience implementing real-time filtering and control algorithms in embedded code • Strong understanding of aerospace system engineering fundamentals. • Hands-on individual who can support systems integration processes and capability to test systems and resolve problems. • Experience with Confluence and JIRA. • Demonstrated capability to efficiently work with little supervision. • Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity. • Demonstrate excellent written and verbal communications skills in English & French work environment.

Location: United States Workplace: Remote ClickHouse is looking for Growth Engineers who are obsessed with both craft UI and agentic experiences. You care about the button, the empty state, and the agent that helps someone get unstuck, and you care equally about whether any of it moved the number. You’ll join our growth pod to build experimentation infrastructure, onboarding flows, and product surfaces across the self-serve funnel: classic human UI and AI-assisted / agent-driven flows. You’ll work side by side with unified console engineers, but your mandate is speed and impact: ship something testable, measure it, and iterate. You’re motivated by moving a number and learning fast, more than by getting every detail right on the first try. This is a new role at ClickHouse. You’ll help define what growth engineering looks like here: PLG experimentation that spans human and agentic experiences. You’ll work closely with product, design, and data science on one pod, and partner with unified console and app teams on shared product surfaces. What you will do: - Build and ship experiments across the self-serve funnel: signup, onboarding, activation, and monetization flows. - Design and polish human UI (flows, forms, empty states, navigation, microcopy surfaces) with a high bar for clarity and conversion. - Design and ship agentic experiences (AI-assisted onboarding, in-product agents, guided workflows) that help users reach value faster. - Run disciplined experiments on both: hypothesis, instrumentation, ship, learn. Tools like GrowthBook are part of the day-to-day. - Partner closely with product, design, and data science to go from idea to shipped experiment quickly. - Work within the Cloud Console codebase alongside unified console engineers, and partner with app teams (including Observability, Agents, and Postgres) on strong end-to-end user flows. - Obsess over metrics: acquisition, activation, and monetization. You want proof that what you shipped moved the needle. Requirements: - Experienced in full-stack product engineering (TypeScript / Node / React), ideally including time on a growth, product, or experimentation-focused team. - Strong proficiency in TypeScript, Node.js, and React, with real taste for product UI. - Experience building with LLMs or agent patterns in a product (tool calling, streaming, evals, system/prompt design), or a clear track record of shipping AI features you measured and iterated on. - Comfortable shipping a smaller, testable version of an idea first, then iterating based on what you learn. - Familiarity with RESTful APIs and JSON. - Experience with experimentation or A/B testing tools (e.g. GrowthBook, Optimizely, LaunchDarkly), or strong interest in building that muscle. - Proficient with Git and collaborative code review. - Excellent communication skills. You’ll work daily with PM, design, data science, marketing, and other engineering teams. Preferred Qualifications: - You’ve shipped both polished UI experiments and agentic / AI-assisted product experiences (not just prototypes), with instrumentation and iteration. - Experience on a growth or product-led-growth team, ideally at a company with a self-serve funnel. - Experience with ClickHouse or other data-intensive/analytics products. - Familiarity with Auth0 or similar auth integrations. - Experience working closely with (but not necessarily reporting into) a separate platform or infrastructure engineering team. - You have opinions on what makes great human UX and great agent UX, and you use AI heavily in your own workflow. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Sainte-Anne-de-Bellevue, Canada Role overview: Our client is seeking a GNC System Engineer for design, integration, verification, and operational support of GNC subsystems for our current and next‑generation remote sensing and communications satellites. The role will require to design the complete subsystem, from algorithm development through hardware implementation, verification, and on‑orbit operation support. The role requires deep expertise in orbital dynamics, attitude‑determination & control, plus real‑time FSW definition and integration, and will work closely with subsystem and mission operations teams throughout the satellite life‑cycle. Tasks summary: Architecture Concept & Requirements Derive GNC functional, performance, and safety requirements (pointing accuracy, slew rate, orbit‑maintenance ΔV, fault‑tolerance) from mission level requirements. Produce System Requirements, Interface Control document (ICD), and Description Document. Perform requirement management and maintain bidirectional traceability throughout the project lifecycle. Modelling & Trade‑Study Conduct trade studies on sensor suites and actuator families. Perform high‑fidelity dynamics simulations (Matlab/Simulink, STK) to meet pointing requirements, maintain error budgets, control‑law stability, fuel consumption, and survivability margins. Algorithm Development Design and implement attitude‑determination algorithms and orbit‑determination solutions. Develop control laws for 3‑axis stabilization, slew maneuvers, station keeping algorithms Validate algorithms with Monte‑Carlo analysis, worst‑case scenarios, and support SIL/HIL testing on avionic test bench. Cross‑Functional Coordination, Stakeholder & Program Interaction Translate algorithms into FSW requirements running on real‑time operating systems. Collaborate with the C&DH and FSW teams to implement TM/TC, schedulers and FDIR logic for GNC. Present technical status, risk analyses, and trade‑study results to senior management. Negotiate and maintain ICDs with subsystems. Support B&P (Phase 0 & pre-phase A). Hardware Selection & Design Specify sensor and actuator hardware, perform interface definition (electrical, mechanical, thermal) and conduct trade on redundancy architectures. Work with structures and thermal engineers to ensure proper mounting, thermal paths, and vibration survivability of GNC hardware aligning with payload requirements. Review harness routing and power distribution for GNC electronics. Integration & Verification (IVV) Author Verification Plans, Test Matrices, and Validation Procedures for unit, subsystem, and spacecraft level GNC tests. Lead functional tests: sensor calibration, actuator command‑response, closed‑loop attitude‑control on testbeds, and on‑orbit checkout sequences. Conduct failure mode and effects analysis (FMEA), fault tree analysis (FTA), and reliability prediction. Technical Leadership & Mentorship Mentor, guide junior engineers and interns. Act as technical liaison with customers, partners and external vendors Act as Continuous Improvement stakeholder Contribute to our client’s knowledge‑base, process enhancements, and standards. Configuration, Documentation & Standards Management Maintain GNC standards (sensor/actuator interface, filter design, control‑law documentation). • Ensure all artefacts, analysis, software, deliverables and documentations are version controlled in PLM environment. Support design reviews (SRR, PDR, CDR, MRR/TRR…etc.). Support Technology Road‑Mapping & Innovation On‑Orbit & Operations Support Support procedure developments (detumble, orbit‑maintenance, safe‑mode…etc.). Provide real‑time GNC support during launch, early‑orbit checkout, and contingency events. Analyse on‑orbit telemetry, update filter parameters, and generate performance reports. • Support SOOH development and associated operator training. Required Qualifications: B.Sc. in Electrical Engineering, Aerospace or Physics, (M.Sc. preferred), focused on flight dynamics, control theory, or navigation with 10+ of GNC/AOCS experience on LEO/MEO/GEO platforms. Orbital mechanics, attitude dynamics, and control‑law design (classical and modern optimal control). Proficiency with navigation sensors and actuators. Experience implementing real‑time filtering and control algorithms in embedded code Strong understanding of aerospace system engineering fundamentals. • Hands-on individual who can support systems integration processes and capability to test systems and resolve problems. Experience with Confluence and JIRA. • Demonstrated capability to efficiently work with little supervision. • Ability to distill complex problems to fundamentals to solve with analysis, similarity, or creativity. • Demonstrate excellent written and verbal communications skills in English & French work environment.

Location: Lithuania; Bosnia & Herzogovina; North Macedonia; Romania; Slovakia; Slovenia; Serbia; Malta; Moldova; Montenegro; Portugal; Estonia; Latvia; Albania; United Kingdom; Czech Republic; Greece; Cyprus; Kosovo; Bulgaria; Poland; Georgia; Bosnia and Herzegovina; Turkey; Croatia; South Africa Workplace: Remote [https://app.ashbyhq.com/api/images/user-content/b540b9e2-0673-4d2d-91fd-e293658f4f6a/b7561393-0797-4849-9149-363b09bab85c/job%20ad%20visual.png] Please be informed that Foxelli Group hires exclusively in-house and doesn't work with any external recruitment agencies. Any company or individual claiming to recruit on behalf of Foxelli Group is not affiliated with us. At Foxelli, we’re building more than e-commerce brands - we’re building a tribe of thoughtful humans: AI enthusiasts, curious builders, and ambitious minds who care about doing meaningful work together. Ten years in, our D2C brands reach millions and generate over $20M annually. Our focus stays simple: create products customers love and a team that actually enjoys building them. If you love to learn, experiment, think boldly, make decisions, and build things that matter - you’ll feel at home with us. WHY JOIN FOXELLI? Foxelli is a place for people who think deeply, learn quickly, automate repetitive work, enjoy spending time together, and build things that matter. We work hard, joke often, and don’t take ourselves too seriously. If you’re excited about AI, eager to learn, and want to create work that genuinely means something with people who care, you’ll feel right at home with us - no matter where you are in your career. What You'll Do We create premium AI short films and series that make people feel something. You'll be a key part of building this, producing daily episodes of dark romance, horror, thriller, and fantasy micro-dramas for TikTok, Instagram Reels, and YouTube Shorts. Each episode is 60-90 seconds of polished, character-driven storytelling that lives on someone's phone, often watched without sound. You'll work at the intersection of cutting-edge AI tools and deliberate creative craft. This means: - Striking visuals that stop the scroll and draw the eye - Believable characters who feel real, episode to episode - Natural-sounding voices and carefully placed audio that works whether the sound is on or off - Purposeful editing where every cut serves the story and the viewer's emotional journey - Style in service of story—the look and feel should match the world and tone of the series You'll move fast, but never at the expense of craft. Every frame should feel intentional What We're Looking For - 2-5 years of professional experience working with AI tools for video, image, or audio generation - Solid understanding of editing fundamentals: frame composition, pacing, visual flow, and how cuts guide audience attention - Prompt engineering skills -ability to write precise, iterative prompts that yield the exact creative output you need - Portfolio demonstrating completed AI-generated video work or traditional video edited to a high standard - Ability to work independently and ship fast without constant creative direction - Familiarity with vertical video format requirements and platform-specific best practices It will be a plus: - Experience in classic video production (films, TV series, shows) - Understanding of dramaturgy and story construction - The full cycle of AI video creation - from idea to final - Experience working with short drama or creating AI content for TikTok / YouTube THE RECRUITMENT PROCESS 1. Apply - A simple form that helps us know who’s stepping into our world. 2. Text Task - A small real-world challenge so we can see how you approach problems in action. 3. Hire - if we align, we'll invite you to join our team for a test trial period. FIXED SERVICE FEE Up to 2500 euros per month after taxes (depending on your skills, competencies, and experience, we'd be happy to negotiate your salary). PERKS & BENEFITS - Full flexibility with your schedule in a fully remote setting, while Hubstaff ensures transparency and fairness. - Complimentary gym memberships and company-sponsored outdoor adventures for your strength and to keep your physical well-being in check. - A personal development budget is at your disposal for your personal and professional growth to ensure you keep growing continuously. - Generous paid time off, including parental leave and vacation days, to recharge and rejuvenate and ensure you’re well-rested. - A budget for your home office setup so you’re comfortable working how you like and where you like. - Strong company culture and a network of unique individuals that celebrate you. ELIGIBILITY & LOCATION REQUIREMENTS ❕This role is 100% remote. - Our tribe works primarily in the Eastern European Time Zone (EET — UTC+2/UTC+3). We also use Revolut for payments, so we are open to hiring candidates in countries where Revolut payments are supported. - For full-time roles, we ask that you’re available for at least 5 hours during typical EET working hours — it keeps collaboration smooth and communication easy. (This doesn’t apply to part-time roles.) Currently, we are hiring in Albania, Bosnia and Herzegovina, Croatia, Czech Republic, Estonia, Greece, Georgia, Kosovo, Latvia, Lithuania, Moldova, Montenegro, North Macedonia, Poland, Portugal, Romania, Slovakia, Malta, Slovenia, Serbia, Cyprus, Bulgaria, Hungary, Netherlands, the United Kingdom, and South Africa.

Location: UK, London 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're hiring a Senior Autonomy Engineer focused on Spatial Intelligence to join our team. In this role, you will bridge the gap between classical spatial geometry and next-generation AI. You will lead the design and development of robust state estimation, long-term mapping, and localisation loops, with a specific focus on integrating modern machine learning techniques and foundation geometry models into our core navigation stack. Your work will ensure our robots possess rock-solid spatial awareness and execute highly reliable trajectories over extended deployments in complex, real-world environments. WHAT YOU'LL DO - Architect the spatial intelligence layer that unifies 3D geometry with semantic scene understanding to ensure safe and efficient navigation and locomotion in complex environments - Develop advanced 3D spatial reasoning capabilities that provide our robots with long-term persistent spatial memory and a deep contextual awareness of their surroundings. - Own the entire perception lifecycle by training large-scale multimodal networks and deploying and integrating them for ultra-low latency performance on edge hardware - Bridge the gap between conceptual research and physical reality by implementing state-of-the-art 3D representations that track and interpret the environment state - Collaborate with cross-functional teams to bridge the gap between large-scale model training and reliable robot integration. - Stay ahead of the field, rapidly evaluate new model architectures, benchmarks, and datasets to guide our embodied AI roadmap. WHAT WE'RE LOOKING FOR - Exceptional software engineering skills with a proven track record of shipping complex ML systems into production. - Strong background in 3D scene understanding and the design of efficient spatial data structures. - Deep experience in machine learning for vision or embodied AI, ideally with large models (VLMs, transformers, or multi-modal architectures). - Proficiency in PyTorch and hands-on experience building, fine-tuning, and deploying large-scale ML systems. - High-impact individual contributor capable of taking projects from conceptual research to high-performance robot code. - Comfortable working in a fast-moving, research-driven environment with evolving models, data, and tools. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Требования: 1) Коммерческий опыт работы от 3-х лет. 2) Опыт реализации и вывода в промышленную эксплуатацию решений на базе ИИ (обязательно в том числе AI агентов на базе LLM) в роли Data Scientist/AI Engineer. 3) Знание основ Classic Machine Learning, хорошее знание Deep Learning (NLP). 4) Глубокое понимание архитектуры Transformer. 5) Глубокое понимание подходов и методов проектирования AI-агентов. 6) Практический опыт fine-tuning языковых моделей (GPT-like, BERT-like и др.). 7) Работа со стеком Python - Torch, Transformers. 8) Опыт разработки интеграций с ИТ-системами. 9) Опыт промышленной работы с k8s. Обязанности: - Артефакты тестирования гипотез/экспериментов: описание подхода/модели, соответствующие значения метрик (выбранных для данного решения), тестовый сет/бенчмарк. - Артефакты продукта в целом: описание проекта, архитектура (утвержденная и согласованная с архитекторами и информационной безопасностью (ИБ)), согласование от ИБ что решение может быть использовано в продакшн, код продукта и документация к нему, инструкция по разворачиванию решения в контуре компании. - Все вышеперечисленные артефакты размещены в контуре заказчика (Gitlab, Confluence).

Location: Raanana Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM Our Growth team is a transversal entity aiming to maximize and deliver the potential of any mobile product. It combines user acquisition, creative content production, monetization, and the tech capabilities required to turn applications into global hits. With over 150 experts, we operate at the forefront of mobile marketing and ad tech across various types of games (hypercasual, hybrid, 100% IAP). ROLE Beach Bum is a dynamic and innovative gaming company that brings a fresh twist to classic games by introducing them to the world of casual online games. Beach Bum was created in 2015 by industry leaders out of a genuine passion for gaming and technology. In 2021, Beach Bum was acquired by Voodoo, opening the door to countless new opportunities and millions of players worldwide! As a the Head of Growth, you will own the scaling of a top priority game or a portfolio of new titles, as a strategic counterpart to the General Manager. Your mission is simple: grow Beach Bum's flagship game aggressively. You will leverage our full Performance Marketing engine (User Acquisition experts, Creative Production, internal tools) and activate non-paid growth levers to push performance even further. - Build and own the growth strategy to scale our leading mobile games. - Execute all our acquisition channels: paid UA but also non-paid such as partnerships, featuring, influencer marketing, growth hacking, ASO, and community building (not exhaustive). - Monitor market trends and competitors to identify emerging high-performing growth channels. - Collaborate with cross-functional teams to ensure flawless execution and maximize the impact of available resources. - Conduct rigorous data analysis to evaluate channel performance, guide decisions, prioritize initiatives, and uncover new growth opportunities. PROFILE - 4-6 years experience on Growth expertise, in a fast-paced, analytical environments (gaming, high-growth tech environments B2C) - Bachelor/Master’s degree from a top engineering or business school. - Strong strategic thinking and analytical capabilities. - Genuine interest in mobile gaming and apps and performance marketing. - Autonomous, proactive, and comfortable rolling up your sleeves. - Excellent communication and interpersonal skills. - Fluent in English and Hebrew, with French considered a strong plus. BENEFITS - Cibus meal card with a monthly allowance of ILS 1,000 - Sick leave starting from the first day of employment - Half-day off on select holiday eves, in addition to statutory and contractual entitlements - An extra vacation day accrued for each year of employment - Company shuttle service from Tel Aviv, Ramat Gan, Givatayim, and Herzliya - Study fund (Keren Hishtalmut) starting from the first day of employment

Дивизион "Моделирование и исследование данных" отвечает за компетенцию Data Science в Блоке Сеть Продаж. Мы разрабатываем и внедряем end-to-end решения на основе AI в бизнес-процессы Сети Продаж Банка. Ищем человека, вместе с которым мы будем строить топовые AI решения, на основе архитектуры Claw-like & Ouroboros, которые будут в действительности приводить к Disrupt в реальных процессах. Задачи: • разрабатывать с нуля AI-агентов и микросервисы для AI-продуктов • исследовать и внедрять новейшие технологические решения в ИИ - Claw-like & Ouroboros • разрабатывать и дообучать модели машинного обучения (Classic ML, Deep Learning) • разрабатывать алгоритмы взаимодействия ML-моделей и сервисных модулей • принимать участие в разработке архитектуры и дизайна агентов и AI-сервисов • проектировать и разрабатывать backend-части AI-сервиса • принимать участие в оптимизации скорости работы AI-агентов и ML-моделей. Мы ожидаем: • законченное высшее образование • компетенции: Python, Classic ML, Deep Learning, LLM/Agents, MLOps • понимание принципов разработки, внедрения и сопровождения AI-решений • уметь писать хороший и понятный production-ready код на Python, хорошее знание алгоритмов, структур данных • опыт работы с реляционными и нереляционными базами данных • навыки работы с генеративными AI-моделями, опыт создания AI-агентов и использование их в работе будет преимуществом • опыт использования GigaChat, Kandinsky и аналогов в продуктах • инструментальное владение Ai для анализа, генерации и автоматизации • опыт построения отказоустойчивых высоконагруженных распределенных ML систем. Мы готовы предлагать: • график 5/2, офис на м. Кутузовская; • режим работы на выбор - офис или гибрид • достойный уровень вознаграждения (оклад + годовая премия) • возможность стать частью команды, реализующей программы цифровой трансформации банка - на основе передового опыта и инновационных идей • широкие возможности для профессионального развития: корпоративный университет и множество онлайн-программ обучения. Корпоративное обучение за счет компании • бесплатная подписка СберПрайм+, многочисленные скидки и бонусы от партнеров: СберМаркет, МегаМаркет, Самокат, Еаптека и др.

Location: San Francisco Bay Area, California; New York City Metropolitan Area Workplace: remote About the role: Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) — people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints. You will do the customer’s job before you automate it. Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it. A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagement in the operator’s seat — as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we’ve been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive and rebuild the function from first principles — and you are the one who builds it. Three things define how you work: Embedded, not engaged . You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Real tasks, not scope . You are not fenced into a siloed deliverable. You go where the operating problem is. Autonomous . Embedded is not staff-augmented. You own the method; nobody hands you a ticket. You won’t start from zero. Provectus builds industry blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice. You’ll be measured on whether the Business Unit’s number moved — not on hours, not on scope delivered. This is a role for engineers who have led before — as a founder, a CTO, a staff engineer — and who want to stay in the code while owning the outcome. On most days you’ll be the most senior technical person in the room, and you’ll still be the one shipping. Requirements: 8+ years building software , a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. You will take the operator’s seat. You are genuinely willing to spend weeks doing someone else’s job — claims processing, underwriting, revenue-cycle work — before you write a line of code. Engineers who need to stay in the IDE should not apply. You learn domains fast. Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Solid AI/ML foundations — you understand what the models do well enough to reason about failure modes, not just call the API. Strong hands-on prodcution experience with Claude Code/Cowork. Fluent English, written and spoken. Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution. Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management . Consulting, professional services, or other embedded customer-facing delivery. Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality. MLOps and classical ML: PyTorch, SageMaker, MLflow. Fine-tuning, distillation, or inference/serving optimization. Graph databases (Neo4j, AWS Neptune). IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Take the seat Do the operator’s job for two to four weeks at the start of an engagement. Learn the function from inside, not from a requirements doc. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow — in weeks, not quarters. Sit with the operator and the Forward Deployed Executive and redesign the function from first principles. Discovery, user research, and PRD-writing collapse into one team that re-imagines its own job. You are all three roles. Build Ship production GenAI systems into the customer’s environment — LLM applications, agentic workflows, retrieval and structured-extraction pipelines, and the services around them. Running software, not recommendations. Build the evaluation harness before you build the feature. When the engagement is bound to a business KPI, “it looked good in testing” is not an answer. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — backend services, data pipelines, and the AI layer. Python and TypeScript are our centre of gravity; we choose tools to fit the customer, not the résumé. Take systems to production on AWS (GCP/Azure where the customer requires it): containerized, observable, and maintainable after we leave. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Own the outcome Work in a pair with a Forward Deployed Executive who carries the Business Unit’s KPIs. Your work is measured against the same number. Drive adoption. A system the BU routes around has not shipped. Change management is part of the engineering job here, not a phase after it. Be credible with the customer’s engineers, their operators, and their executives — and be willing to disagree with all three. Shape what we commit to before we commit to it. You’ll have the standing to do it, because you’re the one who will build it. What We Offer: Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare The chance to shape how leading enterprises adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. OTE range: up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. How we hire: Intro conversation — the role, your background, what you want to be doing. Two live engineering sessions. Real problems, your own editor. You may use an LLM assistant (ChatGPT, Claude) — how you work now includes these tools. Autocomplete/agentic coding tools are off for these sessions. The redesign session. We hand you an unfamiliar business function and the constraints of the person who performs it. You have to understand the job well enough to rebuild it — then say what you’d build and how you’d know it worked. No LLMs for this one. Team and practice conversation.

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Baseten's GTM org is in hyper growth. As it grows and matures, the needs of the GTM stack get more sophisticated with scale — and this team exists to stay ahead of those needs. This role owns a core set of the platforms the field runs on. You'll administer, configure, and continuously improve them, build AI and automation on top of the CRM to keep it clean and current, and run the adoption programs that make sure the field actually uses what we put in front of them. We're an AI-native company scaling fast, and we want to add sophistication without adding drag — you'll be the person deciding how much system is enough. This isn't a classic Salesforce admin role. You know the ecosystem, but you come at it as a builder and an orchestrator, not a ticket-taker. Central RevOps is the systems and operations center of excellence for Baseten's GTM org. The stack includes Salesforce, Pylon, Outreach, Sales Navigator, Clay, and a growing set of AI-native GTM tools. The field is scaling fast, and the systems need to mature with it without slowing anyone down. You'll co-own Salesforce with our other GTM Systems Manager and work alongside a GTM Engineering team who builds internal AI products for GTM productivity — plus partner closely with sales leadership and the field. RESPONSIBILITIES - Own adminship, configuration, and enablement for Pylon, Gong, Sales Navigator, Outreach, and Prospect. These platforms are yours end-to-end — configured well, enabled with the field, and continuously improved as needs grow. - Run adoption, license forecasting, and vendor management for each of those systems. Own the adoption programs that get the field using them, forecast license needs ahead of growth, and manage the vendor relationships and renewals. - Co-own Salesforce. Partner with our other GTM Systems Manager to keep the CRM configured for how sales actually runs, and act as backup for Deal Operations processes. - Build AI and automation on top of the CRM. Stand up agents and automations that update and maintain the CRM — keeping data clean, current, and trustworthy without adding manual work. - Drive adoption, not just deployment. Document what you build, enable the field, and measure success by whether people actually use it. - Right-size the process. Add just enough structure to scale the company without slowing the field down. Have a point of view on where process helps and where it just gets in the way. REQUIREMENTS - 4+ years in GTM systems, RevOps, or sales/business systems — owning platforms and process end-to-end - Experience building AI and automation on top of a CRM — you've built agents or automations that update and maintain CRM data, not just configured fields - Hands-on adminship and configuration experience across a multi-tool GTM stack (support ops, engagement, prospecting, and enrichment tools) - Working knowledge of the Salesforce ecosystem and data model — enough to co-own the CRM — without wanting to be a career admin - A real appetite for enablement — you care whether the field uses what you build, and you'll run the adoption programs to make sure it does - Experience owning vendor relationships, renewals, and license planning - Judgment on process — you can tell structure that helps the field from structure that slows it down, and you right-size accordingly - Experience in high-growth B2B technology companies, ideally scaling systems as the field grows fast NICE TO HAVE - Fluency with AI and automation tooling (Claude, Clay, n8n, or similar) as a builder, not just a user - Familiarity with a data warehouse and BI environment (Sigma, Hex, BigQuery, Snowflake) on the data layer - Hands-on experience with Pylon - Exposure to Deal Operations, CPQ, or quote-to-cash processes as a backup or contributor - You've inherited a sprawling, redundant stack and made it more intentional without breaking what works BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: UK, London 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 Staff Robotics Control Engineer to join our Control Team in London and lead the evolution of whole-body control for our Wheeled Alpha platform - a humanoid whose whole body spans a wheeled base, torso and two arms, controlled as one coordinated system. We need genuine depth in classical whole-body control. You should know hierarchical and weighted QP formulations from the inside - not as a library you have called, but as something you have derived, implemented, tuned, profiled and debugged on real hardware under demo pressure. You should have opinions about strict hierarchies versus soft-weighted stacks, regularisation and nullspace behaviour, what to do when a task set becomes infeasible, and how to keep a redundant system clear of singularities without it feeling sluggish. Alongside that depth, you will set technical direction and mentor a strong team of control engineers. WHAT YOU'LL DO Whole-Body Control Architecture & Algorithms: - Lead the evolution of the Wheeled Alpha whole-body controller: task formulation, prioritisation, weighting, constraint handling and solver selection. - Coordinate wheeled base, torso and dual-arm motion within a single whole-body formulation, with base motion that tracks commanded targets accurately and stays well-behaved under aggressive commands and long-duration operation. - Own the constraint layer - self-collision avoidance, joint and velocity limit guarding, and singularity handling - plus feasibility handling and recovery when the solver fails. - Drive the evolution toward predictive formulations: evaluate and develop MPC-based whole-body control where anticipating dynamics and constraints outperforms instantaneous QP resolution. Dynamics, Compliance & Payload: - Own the dynamic models the controller runs on - inertial, gravity and friction modelling, system identification, and online payload estimation - so the robot knows what it is carrying and controls accordingly. - Advance compliance and force behaviour - impedance, admittance and force control that stays compliant at contact - and extend payload capability without sacrificing either. - Own stability-aware behaviour under changing payload and dynamic motion Safety Integration: - Make whole-body control a first-class citizen of the safety architecture: the controller must accept and honour requests from dedicated safety compute - velocity capping, controlled deceleration, constrained operating envelopes - provably and without degrading motion quality. - Co-own the controls-to-safety interface with the safety team, and design control behaviour so that safety interventions are graceful rather than abrupt. Technical Leadership: - Define the performance metrics for whole-body control and insist on deterministic, reproducible evaluation of every change, in simulation and on hardware. - Mentor control engineers on optimisation-based control, numerical robustness and hardware debugging; act as reviewer of record for the most consequential changes. - Work with hardware teams so control constraints and mechanical design decisions stay coherent. WHAT WE'RE LOOKING FOR - Deep, demonstrable expertise in optimisation-based whole-body control: hierarchical and weighted QP formulations, task prioritisation, constraint handling, and the numerical realities of solving them inside a real-time loop. - Strong command of the classical WBC toolkit - operational space and task-space control, inverse dynamics and IK formulations, redundancy resolution, nullspace projection, impedance and admittance control, contact and force control - and working knowledge of MPC formulations for whole-body or mobile-manipulation control. - Deployed whole-body controllers on real high-DoF hardware (humanoids, mobile manipulators, dual-arm or legged platforms), including coordinating base and manipulator motion. - Practical fluency with QP/NLP solvers and their failure modes: conditioning, infeasibility, warm starting, solve-time budgets, and what to do at the limit. - Strong dynamic modelling foundations: rigid body kinematics/dynamics (Jacobians, dynamics formulations, URDF-based modelling), inertial and friction system identification, and payload/external-load estimation. - Expert modern C++ for real-time control with Python for analysis and prototyping. - Track record of taking control algorithms to production reliability rather than to a paper or a one-off demo, plus demonstrated technical leadership and mentoring. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Ukraine; Poland; Spain; Portugal; Germany; Romania At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Engineering Manager, Applied AI & Machine Learning Engineering to join us as part of our team. About Role PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. As an Engineering Manager, AI/ML, you will support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives. Your primary focus will be resource planning, execution, and people management. You will work closely with project leads, technical leads, functional managers, and product partners to ensure projects are appropriately staffed, plans are realistic, risks are visible, and teams can deliver effectively. You will manage capacity and resource allocation across multiple projects, help coordinate dependencies and priorities, and provide stakeholders with a clear view of delivery progress. Project and technical leads will continue to own product direction and technical decisions. You will also support the career growth and performance of team members. This includes gathering feedback, coaching employees, creating development plans, and contributing to performance, promotion, and compensation reviews. You should have enough AI/ML experience to understand the work, communicate effectively with engineers, and identify technical delivery risks. However, this is not expected to be a hands-on engineering or architecture role. Our Tech Stack & Focus Areas Generative AI & LLMs: Develop and maintain LLM-based solutions for generative features. Classic ML Models: Develop and maintain predictive and classification models for financial data Vector Databases: Implementing efficient storage and retrieval systems for high-dimensional data embeddings. Embeddings: Developing hybrid models to extract insights from diverse data sources. High-Volume Data Management: Engineering systems capable of handling massive, real-time data streams. Work Environment Flexible schedule with participation in team ceremonies and cross-functional collaboration. Time zone: Europe/Kyiv. As a qualified expert, You will: Manage resource allocation and capacity planning across multiple AI/ML projects and operational commitments Partner with project and technical leads to create realistic delivery plans, milestones, and staffing models Maintain a clear view of project progress, dependencies, risks, and resource constraints Help resolve delivery blockers, priority conflicts, and cross-team dependencies Facilitate quarterly and ongoing planning across MLEs and MLOps teams Provide clear delivery and staffing updates to functional managers and other stakeholders Manage and coach engineers through regular one-to-one meetings and career discussions Gather and synthesize feedback from project leads, technical leads, and cross-functional partners Create development plans and support performance, promotion, and compensation review processes Identify team capability gaps and contribute to hiring, onboarding, retention, and workforce planning Foster an inclusive, collaborative, and high-performing team environment Apply Agile, Lean, and Fast-Flow practices to improve team effectiveness and delivery predictability We’re looking for you if you have At least three years of experience in software engineering, AI/ML, or a related field At least three years of experience in people management, engineering management, or technical program leadership Working knowledge of AI/ML modeling, systems and the development lifecycle Experience managing multiple technical projects with shared resources and cross-team dependencies Strong skills in capacity planning, resource allocation, project execution, risk management, and stakeholder communication Experience supporting the performance and career development of technical employees Ability to understand technical discussions and work effectively with MLE and MLOps teams Experience working with distributed or geographically dispersed teams English — Upper Intermediate or higher; Ukrainian — fluent Bonus points Experience managing or supporting MLE and MLOps teams Experience working in a matrix organization with separate people, project, product, and technical leadership roles Experience with planning or allocating engineers across multiple projects Familiarity with production ML, generative AI, semantic search, summarization, prediction, or similar capabilities Familiarity with technologies such as Kubernetes, Docker, Kafka, Airflow, Snowflake, and cloud platforms Experience conducting performance reviews and building employee development plans Experience working with staffing partners, contractors, or blended internal and external teams Experience in fintech, SaaS, market data, or another data-intensive industry What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling clients growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview Steps: Interview with the recruiter EM & HRBP Interview Technical Interview Final сlient Interview.

Location: Portugal; Georgia; Bulgaria; Vietnam; Cyprus; Montenegro Engage with the business objectives behind key tasks: pricing for B2B/B2C, forecasting and optimization of financial and operational metrics, incident prioritization, and improving customer journey efficiency (revenue growth, cost savings, business impact). Drive ML projects end-to-end: from problem definition and formalization to modeling, piloting, and presenting results. Collaborate with data engineers to collect the necessary datasets and assess implementation feasibility. Work with analysts on A/B test design: defining metrics, splits, and interpreting results. Develop models (classic ML and DL, time series, uplift modeling), conduct error analysis and performance evaluation. Prepare models and code for transfer to production infrastructure (deployment and releases handled by the technical team). Take ownership of model quality, monitor key metrics, and collaborate with the team on degradation issues and improvement plans. Requirements 3+ years of experience as a Data Scientist. Proven experience with end-to-end ML projects (ability to oversee the entire process). Strong knowledge of classical machine learning techniques (feature engineering, classification, regression, boosting, etc.). Hands-on experience with uplift modeling and time series tasks (with real business applications). Experience working with business stakeholders and understanding optimization problems: pricing, B2C, LTV, retention, AB testing, and more. Proficient in Python for DS/ML (writing clean, readable code for models and experiments). Confident SQL user (able to build datasets, write joins, and perform data analysis). Nice to have: experience with MLflow/DVC, pipelines (Airflow or similar), anomaly detection/anti-fraud, deep learning (PyTorch/TensorFlow), and model monitoring. Benefits A fully flexible work schedule — there’s no pressure to start work at exactly 9:00 AM; what matters is achieving results and moving forward; Each person in our team is encouraged to choose their preferred work format. You can work fully remotely, come to the office, or choose a hybrid work model; We are an ambitious and supportive team who love what they do, appreciate each other, and grow together; The growth and development of each employee is our priority, so we have internal programs available for adaptation and training, development of soft skills and leadership abilities that are tailored individually to each employee; We also provide partial compensation for employees participating in external training and conferences; In tourism, it's difficult to grow without an excellent knowledge of English, and we support our employees' language learning goals — we organize group and individual lessons, plus speaking clubs with colleagues from all over the world; And, of course, to encourage you to travel more, we offer corporate prices on hotels and other travel services; We prioritize well-being and are committed to supporting the overall health and work-life balance at ETG. As part of this commitment, we provide MyTime Day Off - an extra day off that is designed to give our employees the flexibility to focus on important matters, whether it’s taking care of their health, mental recharge, addressing personal issues, or any other important activities. Learn more about our data protection practices in our Privacy Policy: https://www.emergingtravel.com/career/hr-policy/

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement. We are building the future of live entertainment. We believe that by providing people with the best and highest-quality live streaming experience in entertainment, we can tackle the world’s “problems” better, together! We are seeking an experienced Python Developer (ML) to join our dynamic team ML team. Our technology stack: Languages: Python; Monitoring: Prometheus, VictoriaMetrics, Grafana, Grafana Loki, Sentry; DBs: MariaDB, Clickhouse, Redis; Streaming: Apache Kafka; Workflow management: Apache Airflow, Argo Workflow; Infrastructure: k8s, gitlab. Job Responsibilities Design and build production-grade Python services for running and maintaining ML applications for different domains: RecSys, CV, Classic ML, NLP. Develop and maintain data pipelines for training, validation, batch inference workflows Build internal tools and reusable modules for the ML team Implement monitoring and observability for ML services using metrics, logs, and dashboards. Contribute to continuous integration and delivery pipelines (testing, packaging, and automation). Develop visualization and debugging tools for model outputs — including active learning and content analysis interfaces. Ensure that all components are reliable, testable, and easy to maintain. You’ll thrive here if you have 3+ years of experience as a Python Developer, Backend Engineer, or Data Engineer. Strong Python skills (asyncio, FastAPI, pydantic, typing, modular architecture). Proven experience designing and deploying production systems with Docker, Kubernetes and CI/CD. Familiarity with ML workflows (you don’t need to train models yourself, but you understand how they’re served, retrained, and monitored). Experience building data pipelines and integrating with various data sources. Knowledge of metrics, logging, and observability best practices (Grafana, Prometheus, Loki, etc.). Strong understanding of testing, clean code, and maintainable software design. Qualification that can be a plus: Experience working with machine learning teams or MLOps pipelines. Experience with distributed systems or high-load backend services. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR Interview (40 min); Technical Interview + Live Coding (1.5 hour); Final Interview (1 hour).

Задачи: - Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision, возможен также classic ML. - Анализ и обработка данных. - Работа с PyTorch. - Тестирование и оптимизация моделей. - Подготовка модели к запуску в продакшене, участие в A/B тестах, поэтапных раскатках и мониторинге качества. - Поддержка существующих моделей. Требования: - Широкий прикладной ML-бэкграунд: опыт работы минимум с двумя направлениями из Computer Vision, NLP / LLM, classic ML (обучение моделей, интеграция их в реальные проекты). - Коммерческий опыт в Data Science / ML от 4 лет. - Уверенное знание Python и PyTorch. - Хорошее знание классического ML и современного DL (включая математику за ними). - Опыт самостоятельного ведения задач на разных этапах проекта. - Умение переводить бизнес-задачу в ML-постановку и предлагать практичные решения.

Задачи: - Разработка и обучение ML/DL-моделей для задач NLP и Computer Vision, возможен также classic ML. - Анализ и обработка данных. - Работа с PyTorch. - Тестирование и оптимизация моделей. - Подготовка модели к запуску в продакшене, участие в A/B тестах, поэтапных раскатках и мониторинге качества. - Поддержка существующих моделей. Требования: - Широкий прикладной ML-бэкграунд: опыт работы минимум с двумя направлениями из Computer Vision, NLP / LLM, classic ML (обучение моделей, интеграция их в реальные проекты). - Коммерческий опыт в Data Science / ML от 4 лет. - Уверенное знание Python и PyTorch. - Хорошее знание классического ML и современного DL (включая математику за ними). - Опыт самостоятельного ведения задач на разных этапах проекта. - Умение переводить бизнес-задачу в ML-постановку и предлагать практичные решения