To, nad czym pracujesz dziś, ma wpływ na to, gdzie będziesz jutro. Szukasz nowych wyzwań jako ML Engineer? Mamy coś dla Ciebie! W B3 zaczynamy od ludzi i ich doświadczenia. Dobieramy projekty tak, aby odpowiadały Twoim umiejętnościom i ścieżce rozwoju. Pracujemy w wielu obszarach i technologiach, realizując projekty IT w Polsce i w środowisku międzynarodowym, co pozwala budować doświadczenie w sposób przemyślany, a nie przypadkowy. Jesteśmy częścią międzynarodowej organizacji notowanej na NASDAQ w Sztokholmie, działającej w 11 krajach. W Polsce mamy pełną autonomię. Sami wybieramy technologie, procesy i sposób pracy, zachowując najwyższe standardy. Dołącz do nas już dziś! Co oferujemy? - Pracę w skandynawskiej kulturze opartej o logikę i dialog. - Benefity w obszarze zdrowia i sportu dopasowane do potrzeb. - Speed Coaching, krótkie sesje, które dają nowe perspektywy i rozwiązania. - Treningi sportowe, wewnętrzna drużyna, wspólne zawody. Obszary stanowiska: - Budowa i utrzymanie produkcyjnych serwisów ML w domenie reklamowej - wdrażanie, monitorowanie i zapewnienie stabilności operacyjnej modeli ML w środowisku wysokiego ruchu platformy AdTech. - Orkiestracja procesów ML Engineering - zarządzanie cyklem życia modeli, packaging, strategie deploymentu, observability oraz współpraca z zespołami Data Science i Research. - Praca na platformie GCP w środowisku kontenerowym - wykorzystanie Vertex AI, BigQuery i Cloud Storage do obsługi workloadów ML na dużą skalę, z gotowością na on-call i incident management. Czego potrzebujesz, żeby do nas dołączyć: Must have: - Biegłość w podstawach inżynierii oprogramowania oraz produkcyjnych standardach kodowania, ze szczególnym naciskiem na modularną i łatwą w utrzymaniu architekturę. - Doświadczenie we wdrażaniu i utrzymaniu modeli ML w środowiskach produkcyjnych, w tym automatycznym monitorowaniu i rozwiązywaniu incydentów. - Zaawansowana wiedza z zakresu MLOps, obejmująca automatyzację cyklu życia modeli, CI/CD oraz procesy wydawnicze (release management). - Znajomość platform chmurowych (preferowane GCP) do obsługi danych i obciążeń ML na dużą skalę. - Zaawansowana znajomość Pythona i SQL w kontekście inżynierii ML – w szczególności do orkiestracji trenowania i wspierania inferencji. - Dogłębna znajomość zasad DevOps oraz Service Reliability Engineering (SRE) stosowanych w systemach ML. - Umiejętność wykorzystywania narzędzi do kodowania wspomaganych przez AI w celu zwiększenia produktywności inżynierskiej i utrzymania wysokiej jakości kodu. - Angielski: B2+ Nice to have: - Doświadczenie w AdTech, systemach rankingowych lub rekomendacyjnych opartych na ML. - Doświadczenie z rozproszonymi potokami przetwarzania danych i cech (np. Vertex Pipelines, Dask lub Spark). - Znajomość ekosystemów serwowania w chmurze, architektury mikroserwisowej oraz wzorców integracji modeli między różnymi językami programowania. - Doświadczenie z feature store'ami oraz mechanizmami zapewniania spójności między trenowaniem a serwowaniem.

To, nad czym pracujesz dziś, ma wpływ na to, gdzie będziesz jutro. Szukasz nowych wyzwań jako Team Leader (obszar ML, AdTech)? Mamy coś dla Ciebie! W B3 zaczynamy od ludzi i ich doświadczenia. Dobieramy projekty tak, aby odpowiadały Twoim umiejętnościom i ścieżce rozwoju. Pracujemy w wielu obszarach i technologiach, realizując projekty IT w Polsce i w środowisku międzynarodowym, co pozwala budować doświadczenie w sposób przemyślany, a nie przypadkowy. Jesteśmy częścią międzynarodowej organizacji notowanej na NASDAQ w Sztokholmie, działającej w 11 krajach. W Polsce mamy pełną autonomię. Sami wybieramy technologie, procesy i sposób pracy, zachowując najwyższe standardy. Dołącz do nas już dziś! Co oferujemy? - Pracę w skandynawskiej kulturze opartej o logikę i dialog. - Benefity w obszarze zdrowia i sportu dopasowane do potrzeb. - Speed Coaching, krótkie sesje, które dają nowe perspektywy i rozwiązania. - Treningi sportowe, wewnętrzna drużyna, wspólne zawody. Obszary stanowiska: - Dostarczanie wysokiej jakości rozwiązania ML Scoring (np. przewidywanie kliknięć i konwersji) dla Sponsored Offers zgodnie z harmonogramem, przy zachowaniu odpowiedzialności za wyniki techniczne zespołu oraz kamienie milowe projektu. - Zarządzanie zakresem trenowania modeli deep learning, w tym definiowanie zakresu developmentu i standardów model lifecycle. - Transfer odpowiedzialności za scoring od istniejących zespołów we współpracy z interesariuszami z obszaru backendu i produktu. - Dostarczanie eksperckich wskazówek do roadmapy w zakresie ML dla Sponsored Offers. Czego potrzebujesz, żeby do nas dołączyć: Must have: - 8+ lat doświadczenia w rolach związanych z Machine Learning lub Data Science w środowiskach produkcyjnych. - 2+ lata bezpośredniego doświadczenia w zarządzaniu ludźmi. - Udokumentowane osiągnięcia w prowadzeniu inicjatyw end-to-end dotyczących trenowania modeli dla business use cases. - Praktyczna wiedza obejmująca pełny cykl życia modelu: przygotowanie danych, inżynieria cech, trenowanie, ewaluacja, kalibracja i kontrolowane wdrożenie. - Biegłość w Pythonie i SQL, wraz z gruntownym zrozumieniem frameworków ML/deep learning (np. PyTorch lub TensorFlow) oraz skalowalnych procesów przetwarzania danych. - Doświadczenie w obsłudze ML workloads w środowiskach chmurowych, najlepiej GCP (Vertex AI, BigQuery, Cloud Storage). - Zdolność do prowadzenia wielofunkcyjnej realizacji projektów w obszarach ML, modeli i produktu, zapewniając strategiczne dopasowanie i widoczność wyników dla interesariuszy na poziomie dyrektorskim. - Podejmowanie decyzji w oparciu o biznesowe wskaźniki wpływu (przychód, GMV, konwersja) oraz wyniki eksperymentów. - Angielski B2+. Nice to have: - Doświadczenie w obszarze AdTech lub w produktach rankingowych/rekomendacyjnych. - Doświadczenie w zarządzaniu produktami opartymi na platformach eksperymentowania i testach A/B. - Doświadczenie we współpracy z zespołami platformowymi w zakresie roadmap dotyczących danych i możliwości ML. - Znajomość ograniczeń i kompromisów związanych z monetyzacją opartą na aukcjach.

Primary Responsibilities ‍ - Define the AI Roadmap: Collaborate with founders and Product Leads to translate business goals into a technical AI strategy, prioritizing high-impact capabilities for cloud security. - Architect & Lead Development: Take full ownership of the AI-powered product architecture, from the core LLM orchestration to production deployment and monitoring. - Mentor and Grow the Team: Lead code reviews, establish engineering best practices for ML/AI, and mentor other engineers to foster a culture of technical excellence. - Design Advanced AI Agents: Lead the creation of specialized, autonomous agents for cloud-security tasks, ensuring they operate within strict frameworks of permissions, guardrails, and safety. - Champion Multi-Cloud Integration: Oversee the end-to-end flows from "user intent" to "actionable outcome" across AWS, Azure, GCP, and OCI at an enterprise scale. - Establish Rigorous Evals: Define and maintain the framework for measuring model quality (accuracy, hallucination rates, latency, and cost) and ensure these metrics drive our iteration cycles. - Applied Innovation: Stay ahead of the curve in LLMs/Agents, evaluating new papers and technologies to adopt what is practical and secure, while ignoring the hype. ‍ Qualifications / Skills / Experience ‍ ‍ We evaluate the following in candidates for this role: - 5+ years of experience in cloud security, cloud engineering, or building complex security products for cloud environments. - Proven Leadership: Previous experience leading technical teams or serving as a Lead Engineer on high-stakes AI/ML projects. - Expert Cloud Security Knowledge: Deep, hands-on understanding of IAM (policies, federation), Network security, and Cloud Governance (Policy-as-Code). - Elite Coding & Architecture Skills: Ability to design and implement end-to-end production systems that are scalable, maintainable, and secure. - Senior AI Expertise: Extensive experience building with modern AI stacks (LLMs, RAG, structured outputs, agentic workflows, and custom evaluation frameworks). - Pragmatic Instincts: Expert at making trade-offs between speed, cost, and quality, with a "shipping" mindset that never compromises customer trust. - Exceptional Communication: Ability to articulate complex technical visions to both engineers and non-technical stakeholders. - Language Skills: Working fluency in English is required; Spanish is a plus. ‍ Good to have - Experienced with Azure, or Google Cloud - Skilled in advanced Cloud Security frameworks - Experience with advanced ML Ops - Background in Open Source projects ‍ How will you know you are successful in this role? ‍ - Architectural Excellence: The AI infrastructure you design is recognized by the team as robust, scalable, and easy to build upon. - Team Velocity & Growth: You have successfully unblocked and mentored other engineers, increasing the team's ability to ship high-quality AI features. - Industry-Leading Reliability: Our AI agents are trusted by customers to operate in sensitive cloud environments with minimal error rates. - Strategic Impact: You can demonstrate a direct link between your technical decisions and the company’s growth in the multi-cloud security market. ‍ Why join Prowler ‍ - Opportunity to work with a rapidly growing and innovative company in the cloud security industry. - Fully remote work, allowing for a flexible and collaborative environment. - Competitive compensation package. - Continuous learning and professional development opportunities. - Be part of a dynamic team that values creativity and innovation. ‍ Work Hours & Benefits ‍ This is a full time, salaried position writing, testing, reviewing, and operating code at scale. Prowler is fully remote and distributed, spanning all U.S. time zones and several in E.U. This necessitates individuals taking responsibility for their working hours and broadcasting availability to colleagues. Mandatory minimum PTO (shoot for ~5 weeks; anything less than 4 weeks/year is unacceptable), workstation/home office stipend per year, flexible working hours, and stock options are some of our other benefits. ‍ Hiring Process ‍ - Intro/Technical Screen: If you are interested in this role, we would love to meet you for a 30 min call with one of our founders or tech leads. You will be invited to talk about your experience and the challenges you have faced as a professional. (30 minutes) - Cultural Interview: We have a generative, diversity-focused culture that highly prioritizes context over control. Not everyone prefers this type of environment, and this interview ensures that you are comfortable with the freedoms and responsibilities we expect of our colleagues, and that you can thrive here. (1 hour) - Architecture & AI Deep Dive: A practical session focused on designing a complex AI agent system or solving an architectural challenge within a cloud security context. (1 hour) ‍

We’re on a mission to change the future of clinical research. At Perceptive, we help the biopharmaceutical industry bring medical treatments to the market, faster. Our mission is to change the world but to do this, we need people like you. What can we offer you? Apart from job satisfaction, we can offer you: YOURSELF • 25 days’ holiday (with the option to buy more) HEALTH • Health Cash Plan • Optional private health, dental insurance, and health screens • Cycle to work scheme WEALTH • Generous pension scheme with up to 10% employer contribution • Life assurance • Season ticket loan About the role Job Purpose As Associate Director, AI/ML Engineering, you'll lead the development and integration of cutting-edge artificial intelligence and machine learning (AI/ML) solutions into our Imaging platform for clinical trials. Your role will be central to driving the digital transformation of our platform—enhancing data-driven decision-making, accelerating trial execution, and improving outcomes. You'll lead a multidisciplinary team of engineers and scientists, shaping and executing an ambitious AI/ML strategy aligned with our R&D roadmap. You'll be responsible for defining technical architecture, establishing best practices and championing AI/ML capabilities across the organization. An accomplished professional, you'll play an instrumental role in managing talent, fostering innovation and cultivating a culture of technical excellence and collaboration. Key Responsibilities Strategic and Organizational leadership - Sets the strategic direction and supports the strategic roadmap for AI/ML adoption and innovation within the organization. - Contributes to governance frameworks and recommended protocols for responsible, ethical and sustainable development and use of AI. - Contributes to the development of organizational capabilities, policies, standards and guidelines in AI. - Collaborates with senior stakeholders to identify high-impact opportunities for AI and drives their implementation. - Follows research and industry trends and integrates them into organizational practices. - Works closely with senior leaders within RD to align engineering goals with broader organizational objectives and demonstrates leadership by contributing to strategic discussions. - Serves as a key thought partner to senior leadership, providing regular updates on AI/ML initiatives, progress, risks, and opportunities. Talent growth and People Leadership - Builds a team that drives innovation, aligns with Company culture and values, and delivers business priorities. - Develops a comprehensive talent strategy that includes recruitment, retention, onboarding, and career development. - Leads, mentors, and manages a high-performing team of engineers, fostering an environment that encourages learning, collaboration, and innovation. - Focuses on nurturing future leaders and provides growth opportunities through coaching, training, and mentorship. Cross functional collaborations - Serves as an AI/ML evangelist across the organization, promoting awareness and understanding of the capabilities and value of AI/ML technologies. - Partners with scientists, domain experts, software engineers and product teams to define requirements. - Supports Product Manager to Translate business requirements into technical AI solutions. - Communicates complex technical concepts to technical and non-technical stakeholders. Technical leadership & Mentorship - Oversees the end-to-end lifecycle of AI/ML projects, from concept and design through to deployment and optimization, ensuring timely and successful delivery. - Provides strategic technical direction for AI/ML initiatives, ensuring alignment with the broader R&D and platform transformation goals. - Provides technical leadership and mentorship, guiding engineers in implementing scalable, secure, robust, and high-performing AI/ML systems for clinical trials applications. - Leads code and model reviews, ensuring high standards of quality, performance, and documentation. - Fosters a collaborative and inclusive team culture that encourages innovation, continuous learning, and knowledge sharing, encouraging the exploration of new tools, technologies, and methodologies. - Ensures adoption of ML-Ops best practices, including model versioning, testing, deployment, and monitoring. - Supports the team in identifying the state-of-the-art AI technique (ML, Deep Learning, genAI …) and the needed data sets, to solve the business problem. Innovation & Research application - Stays current with AI/ML research advances and evaluates their practical applications. - Identifies opportunities to improve existing systems with new techniques. - Contributes to the company’s intellectual property through innovative solutions. - Publishes and presents work at conferences. Functional Competencies (Technical knowledge/Skills) - Excellent understanding of machine learning algorithms, neural network, and statistical analysis. - Strong numerical/statistical background including image processing. - Strong source code management skills with git. - Strong programming skills in languages such as Python and/or C++. - Demonstrable ability to challenge work (such as identifying and adding new custom features with improved timelines). - Knowledge of MLOPs tools and practices for continuous integration/deployment of ML models. - Excellent interpersonal, verbal and written communication skills. - A flexible attitude with respect to work assignments and new learning. - A self-starter and able to work under own initiative. - Ability to plan own work to meet given objectives and processes. - Ability to handle production support work. - Ability to manage multiple and varied tasks and prioritize workload with attention to detail. - Shows initiative and self-confidence, is adaptable and able to manage changing and evolving priorities. - Ability to work methodically in a fast-paced, time-sensitive environment. - Demonstratable ability to apply critical thinking to problems and tasks. - Proactively participates in skills improvement training. - Ability to coach and mentor others to succeed enhancing individual and professional development. Sharing knowledge, skills, and expertise to others. - Ability to manage a globally distributed and multi disciplined team, including motivating, developing and coordinating team members. - Ability to identify the appropriate leadership style to manage the individuals in their team. - Strong problem-solving skills and analytical thinking ability. - Leadership potential, attention to detail, and passion for innovation. - Maintains an up-to-date awareness of trends, tools, technology, techniques and processes that affect technology within the Life sciences domain. Behavioural Competencies - Accountability - Adaptability - Customer focus - Robust - Decision Making - Business Acumen - Dealing with ambiguity - Organizational agility - Building effective teams Experience and Certifications - Proven experience in developing and deploying AI/ML solutions in real-world applications with demonstrable experience of productizing AI/ML models. - Proven experience in leading and developing AI/ML teams. - Expertise in Machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. - Strong experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies. - Strong background in data structures, algorithms, and software engineering principles. - Strong experience with medical imaging modalities (such as CT, MRI, PET, or SPECT) and DICOM standard. - Experience with feature stores and ML data pipelines. Education - Ph.D. or Master’s degree in a relevant field (such as Mathematics, Computer Science, Data Science, Software Engineering, Biomedical Engineering, etc.). - English: Fluent. Come as you are. We're proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, colour, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.