Jobs Data Science

We are looking for a Senior AI/Machine Learning Engineer to join a healthcare project from the Netherlands focused on simplifying preparation for orthopedic surgeries. The product uses artificial intelligence to automatically analyze 3D images of the skeletal system and support surgical planning. In this role, you will focus on continuing and improving the X3D pipeline (X-ray to 3D bone reconstruction) and integrating it into the web application.
 

Requirements:
— 5+ years of commercial experience in Machine Learning/AI engineering.
— Strong experience with PyTorch and deep learning model training, evaluation, and optimization.
— Solid background in medical image analysis (CT, X-ray) and/or 3D computer vision.
— Strong understanding of image processing fundamentals, including registration, segmentation, and data augmentation techniques.
— Familiarity with GAN architectures (Pix2Pix, CycleGAN) and encoder-decoder networks.
— Experience working with medical imaging file formats (NIfTI, DICOM).
— Ability to read and implement techniques from research papers.
— Proficiency in Python and scientific computing libraries (NumPy, SciPy, SimpleITK or similar).
— Self-directed and independent working style with the ability to effectively collaborate under technical guidance.
— Upper-Intermediate or higher level of English (spoken and written).

Nice to have:
— Experience with 3D shape reconstruction or 3D mesh processing.
— Familiarity with DRR generation from CT volumes.
— Experience with Azure ML or similar cloud ML platforms.
— Background in orthopedic or musculoskeletal imaging.
— Experience in a medical device or regulated environment (FDA, CE).

Responsibilities:
— Improve and extend the existing X3D pipeline for X-ray to 3D bone reconstruction.
— Design, train, evaluate, and optimize deep learning models for medical image analysis and 3D reconstruction tasks.
— Work with medical imaging data (CT, X-ray, DICOM, NIfTI) and implement preprocessing, augmentation, segmentation, and registration techniques.
— Research, prototype, and implement new approaches from academic papers and industry best practices.
— Integrate machine learning solutions into the web application and support deployment workflows.
— Collaborate closely with the Head of Engineering to further develop and productionize the existing AI pipeline.
— Maintain code quality through testing, documentation, and continuous improvement of ML infrastructure and development processes.

Interview stages:
— HR interview (30 minutes).
— Technical interview (1 hour).
— Interview with the customer (1 hour).
— Job offer 🎉🎉🎉

We offer:
— Competitive salary.
— Challenging tasks and projects.
— Opportunities for professional development and growth.
— Flexible working hours.
— New hardware.
— Free English lessons.
— Table tennis and yoga classes.
— Availability of generators and Starlinks in the office.
— Small gym in the office.
— Adjustable height tables.
— Regular office fruit delivery and other benefits.

Let’s create value together!

Milionyx is a full-cycle iGaming company. We bring together in-house technology development, performance marketing, analytics, and operational expertise.

We are looking for a Senior Data Scientist to become a key contributor to our Marketing Analytics team. The primary focus of this role is building predictive models that optimize user acquisition, evaluate traffic quality, forecast user value, and maximize marketing ROI.
Our product operates on a white-label solution, so the ideal candidate should be comfortable handling heterogeneous datasets, and developing scalable analytical and ML-solutions.

Responsibilities:
Develop and maintain predictive models for:

• LTV, Early LTV Prediction
• ROAS
• Marketing Payback Period
• FTD Prediction
• Deposit behavior forecasting
• Churn Prediction;
• Analyze traffic quality across acquisition channels and identify optimization opportunities;
• Build user value prediction models using early lifecycle behavioral signals;
• Build ML-solutions to optimize marketing budget allocation;
• Collaborate closely with Marketing, Retention, Product, and Tech Teams;
• Monitor model performance, retrain models when necessary, and support production ML-pipelines.

Required Experience:

• 3+ years of experience as a Data Scientist;
• Strong background in Marketing Analytics, User Acquisition, or Growth Analytics;
• Hands-on experience building predictive models for user behavior and business value forecasting;
• Experience delivering ML-solutions from research through production;
• Experience working with large-scale datasets;
• Ability to work with incomplete and heterogeneous data.

Required Technical Skills:

• Python (Pandas, NumPy, Scikit-learn);
• Advanced SQL;
• Git/GitLab;
• Gradient Boosting (XGBoost, LightGBM, CatBoost);
• Random Forest;
• Logistic Regression;
• Customer Segmentation & Clustering;
• Time Series Forecasting (preferred);
• Uplift Modeling (preferred).

Nice to have:

• AWS ecosystem;
• Amazon Athena;
• Apache Kafka;
• GTA (internal analytical data platform);
• Large-scale event-based datasets.

We offer

• Flexible work format — remote, hybrid, or office in Kyiv, whichever suits you best
• Monday–Friday schedule, 10:00 AM–6:00 PM
• 18 days of paid vacation, 10 sick days
• Direct communication with leadership and real influence on marketing and business decisions, without unnecessary bureaucracy

Preferred: Time-zone overlap with India working hours

Important: this is a Core AI R&D role requiring both strong applied ML engineering experience and research-level scientific depth. We are looking specifically for candidates with a research scientist mindset — someone who actively reads and publishes in relevant ML domains, understands state-of-the-art literature, and has demonstrated experience translating research ideas or papers into production-grade systems. Purely applied ML, analytics, or “model usage” backgrounds will not be a fit!
 

About the Opportunity

Our client is a fast-growing technology company developing advanced AI-powered solutions for industrial analytics and operational intelligence. As they continue to expand their Core AI Research & Development team, we are seeking a Senior Data Scientist with strong research and applied experience in one or more of the following areas:

• Time-series modeling for industrial sensor data
• Reinforcement learning and prescriptive decision-making
• Knowledge representation, graph learning, and multi-modal AI systems

This role offers the opportunity to work on cutting-edge AI research while driving real-world business impact through production-grade solutions.
 

Key ResponsibilitiesTime-Series Modeling

• Develop and enhance modern deep learning models for time-series analysis using large-scale industrial sensor datasets.
• Design retraining and adaptation pipelines to maintain model performance as data evolves over time.
• Apply transfer learning and low-label adaptation techniques to support new equipment types and sensor sources.
• Improve prediction accuracy across multiple asset categories.
   

Reinforcement Learning & Prescriptive Intelligence

• Design reinforcement learning frameworks that generate actionable operational recommendations.
• Develop optimization approaches that balance multiple business and operational constraints.
• Implement preference-learning techniques leveraging expert feedback and validated operational outcomes.
• Collaborate with product and engineering teams to integrate prescriptive recommendations into production environments.
   

Knowledge Representation & Multi-modal AI

• Expand and enhance domain knowledge graphs representing industrial assets, failure modes, and recommended actions.
• Apply graph-based learning methods to improve reasoning and knowledge transfer across equipment types.
• Integrate structured and unstructured data sources, including technical documentation, engineering diagrams, operator notes, and conversational data.
• Identify patterns and insights that improve model generalization across industries and customer segments.
   

Research & Collaboration

• Translate state-of-the-art research into scalable, production-ready solutions.
• Mentor junior data scientists and contribute to the growth of the research organization.
• Collaborate with cross-functional teams to bring AI innovations into customer-facing products.
• Define, monitor, and improve quality metrics for predictive and prescriptive AI systems.
• Contribute to patents, publications, and open-source initiatives where appropriate.
   

Required Qualifications, Education

• PhD preferred, or Master’s degree in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, or a related field.
• Exceptional candidates with equivalent industry experience will also be considered.
   

Technical Experience

• 5+ years of hands-on machine learning experience with deep expertise in at least one of:
  • Time-series modeling
  • Reinforcement learning
  • Graph machine learning and knowledge representation
• Strong Python programming skills.
• Experience with modern deep learning frameworks (PyTorch preferred).
• Practical knowledge of reinforcement learning methodologies and production-grade RL frameworks.
• Experience working with knowledge graphs, graph neural networks, embeddings, or related technologies.
• Familiarity with retrieval-augmented systems, vector databases, and unstructured data processing.
• Experience with cloud platforms and managed machine learning services.
• Strong software engineering practices, including version control, testing, and reproducible experimentation.
   

Soft Skills

• Strong product mindset with the ability to move research into production.
• Excellent communication skills and ability to work with both technical and non-technical stakeholders.
• Comfortable working in fast-paced environments with evolving priorities.
• Experience collaborating across distributed and international teams.

Nice to Have

• Experience in predictive maintenance, condition monitoring, industrial AI, or vibration analysis.
• Knowledge of physics-informed machine learning or causal inference techniques.
• Publications in leading ML conferences or journals.
• Experience with agentic AI systems, LLM evaluation, or advanced generative AI applications.
   

What Our Client Offers

• Opportunity to work on challenging AI research problems with direct business impact.
• Collaborative environment combining research excellence with product delivery.
• Remote-first culture with a globally distributed team.
• Exposure to large-scale industrial datasets and real-world AI applications.
• Competitive compensation package and long-term growth opportunities.
   

Looking forward to your reply!

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a Senior Data Scientist to develop predictive models and quantitative analytics that power risk-based vulnerability prioritization within a large-scale enterprise security program. You will structure and analyze massive security telemetry datasets, build ML algorithms to eliminate scanning noise and false positives, and establish unified data dashboards to drive adoption of data-driven security governance. The role requires 5+ years of data science experience with direct commercial application to vulnerability management, operating with full autonomy.

What you will do

• Develop predictive models and quantitative analytics to prioritize vulnerabilities based on contextual risk and business impact;
• Structure and analyze massive outputs of security data from across the enterprise ecosystem to support the ASPM framework;
• Create machine learning algorithms or statistical models to automatically identify and filter out scanning noise and false positives;
• Establish a unified data delivery structure and dashboards to drive the adoption of data-driven security governance.

Must haves

• 5+ years of commercial data science experience, operating completely autonomously with no required supervision;
• Advanced proficiency in Python, R, and SQL;
• Experience with machine learning frameworks such as TensorFlow and PyTorch;
• Experience with data visualization tools;
• Commercial experience applying data science to vulnerability management;
• Upper-intermediate English level.

Nice to haves

• Familiarity with Cloud Security Posture Management (CSPM) data outputs (e.g., Wiz).

The benefits of joining us

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
• Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates

If it’s a match — you’ll get an offer!

We’re looking for a Senior Machine Learning Engineer to design and scale production ML systems that power real-time personalization and decision-making at scale.

In this role, you’ll own the full ML lifecycle—from transforming raw behavioral data into meaningful features, to deploying low-latency prediction APIs, to building the observability needed to keep models reliable in production.

This is a great opportunity for someone with strong applied ML and MLOps expertise who enjoys solving complex engineering challenges and building scalable, high-impact systems.

Your responsibilities will include:

• Build and productionize ML models for ranking, personalization, and customer engagement.
• Develop pipelines that transform behavioral, demographic, and contextual signals into online and offline features.
• Design and deploy low-latency APIs and decision services for real-time decision-making.
• Implement experimentation frameworks, including A/B testing and exploration-exploitation strategies.
• Operationalize the ML lifecycle: automated training, CI/CD for models, artifact and feature versioning, and online/offline parity.
• Build observability into ML systems by monitoring data quality, model drift, and decision outcomes, and triggering retraining when needed.
• Establish closed feedback loops that connect decisions to business outcomes (e.g. conversions, engagement, fatigue signals such as unsubscribes).
• Collaborate closely with product and engineering teams to balance personalization, compliance, and business value in real-world systems.

What we expect from you:

• 5+ years of experience in applied ML engineering (recommendation systems, personalization, ranking, or advertising systems).
• Strong proficiency in Python or Go, SQL, and modern ML frameworks such as TensorFlow, PyTorch, or similar.
• Strong understanding of MLOps best practices, including CI/CD for ML, containerization (Docker), orchestration (Kubernetes, Airflow, Kubeflow), model registries, and monitoring frameworks.
• Familiarity with cloud ML platforms such as Vertex AI, SageMaker, or similar, and data warehouses like BigQuery, Snowflake, or Redshift.
• Experience deploying real-time ML systems, including low-latency serving, feature stores, and event-driven architectures.
• Understanding of multi-objective optimization and trade-offs in personalization systems.
• Comfort working cross-functionally in a dynamic startup environment with the overlap within USA time zone.
• Strong spoken and written English communication skills.

Nice to have:

• Experience in martech, adtech, CRM, or large-scale personalization platforms.
• Exposure to bandit algorithms, reinforcement learning, or causal inference for adaptive decision-making.
• Experience building systems serving millions of users at scale.
• Hands-on experience with Google Cloud Platform (GCP).
• Familiarity with observability tools such as Prometheus, Grafana, Evidently, WhyLabs, or Great Expectations for monitoring data and model health.

What we offer:

• Interesting projects and technical challenges that support both professional and personal growth.
• A long-term project with stability and impact.
• A flexible, results-oriented schedule with hybrid or remote work options.
• A comfortable, modern office in Kyiv with generator and battery backup.
• Competitive salary, medical insurance, and a supportive onboarding/trial period.
• Team-building events, including parties, online activities, picnics, and more.
• The opportunity to work in a Top Employer company (DOU 2025).

Workload: minimum 50%, up to 80–100% !!!
Start: after summer holiday period (early autumn)
Duration: long-term assignment (exact length to be confirmed)
Location: flexible / hybrid (EU-based collaboration expected)
English: B2


Description:
We are looking for an experienced Senior Data Architect to define a reusable and scalable data foundation supporting sustainability, EHS, and product compliance use cases within a global manufacturing environment.

This assignment focuses on building a governed data architecture that enables automation of lifecycle-related calculations and reporting (such as LCA, product carbon footprint, and environmental declarations), while also supporting broader sustainability reporting, regulatory compliance, and future digital product requirements.

Responsibilities:

• Define the target data architecture and reusable data foundation
• Identify and structure key data domains and data products
• Design data ownership and governance models
• Establish principles for:
• Data quality and validation
• Data lineage and traceability
• Versioning and auditability
• Ensure a modern lakehouse platform acts as the governed backbone for trusted data
• Enable integration of external calculation and authoring tools where appropriate
• Collaborate across business and IT domains to avoid fragmented point-to-point integrations
• Support the creation of reusable, auditable data products for multiple stakeholders

Required experience !!!!!:

• Strong experience in data architecture and modern data platforms (lakehouse)
• Hands-on knowledge of data governance, data products, and domain-driven data design
• Experience working with manufacturing, product data, or industrial environments
• Understanding of sustainability reporting and/or compliance-driven data requirements
• Ability to work across multiple stakeholders: business, IT, data, and compliance teams
• Experience integrating data across systems such as ERP, PLM, and analytics platforms

Nice to have:

• Experience with sustainability-related domains (e.g. lifecycle assessment, carbon footprint, environmental reporting)
• Experience with compliance-driven data (e.g. chemical, product, EHS)
• Familiarity with emerging requirements such as Digital Product Passport

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding its team in Central Europe and is looking for talented Data Science Engineers to join us. Our projects span multiple domains, including data analysis, fintech, computer vision, image processing, edge-device solutions, Large Language Models (LLMs), and classical Machine Learning applications. We build custom Data Science solutions for clients across various industries, combining strong engineering practices with a research-driven mindset.

Joining Quantum means becoming part of a team that values solid technical fundamentals, continuous learning, and practical problem-solving. You'll collaborate on impactful products, work with cutting-edge technologies, and contribute to projects that turn complex ideas into real-world solutions.

Must have skills:

• 3+ years of commercial DS/ML experience
• Solid foundation in linear algebra, statistics, and probability
• Strong Python, including NumPy, Pandas, and scikit-learn
• Hands-on experience with PyTorch (or TensorFlow)
• Deep experience in at least one of: 
  • Computer Vision (modern DL: detection, segmentation, classification - ViT, YOLO, SAM); 
  • LLMs / NLP (fine-tuning, RAG, prompt engineering, embeddings, evaluation); 
  • Classical ML at scale (tabular, time series, recommender systems)
• Working knowledge of Transformers and attention; familiarity with CNNs
• Experience deploying models to production (Docker, REST/gRPC serving, basic monitoring)
• Experience with at least one cloud platform (AWS, GCP, or Azure)
• Clean code and Git workflow
• Experience with SQL
• Upper-Intermediate English (B2+) - you'll communicate directly with clients

Nice to have skills:

• Cross-domain exposure: if your main strength is CV, some LLM exposure is a plus (and vice versa)
• Edge deployment: TensorRT, OpenVINO, ONNX, quantisation, model distillation, mobile/embedded inference
• LLM tooling: LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LoRA/QLoRA fine-tuning, agentic frameworks
• MLOps & model monitoring: MLflow, DVC, Weights & Biases, CI/CD for ML
• Classical CV with OpenCV (still relevant for hybrid pipelines and edge work)
• Ability to read recent papers and implement methods in new domains
• Experience working with external clients
• Participation in Kaggle competitions

Your tasks will include:

• Own full-cycle DS projects: scoping with the client, data prep, modelling, evaluation, deployment
• Build solutions across CV, LLM/NLP, and classical ML depending on the project pipeline
• Deploy models to production - cloud, edge, or hybrid, depending on client needs
• Read recent research and adapt methods to client problems
• Communicate technical decisions and trade-offs directly to clients

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

Workload: minimum 50%, up to 80–100% !!!
Start: after summer holiday period (early autumn)
Duration: long-term assignment (exact length to be confirmed)
Location: flexible / hybrid (EU-based collaboration expected)
English: B2


Description:
We are looking for an experienced Senior Data Architect to define a reusable and scalable data foundation supporting sustainability, EHS, and product compliance use cases within a global manufacturing environment.

This assignment focuses on building a governed data architecture that enables automation of lifecycle-related calculations and reporting (such as LCA, product carbon footprint, and environmental declarations), while also supporting broader sustainability reporting, regulatory compliance, and future digital product requirements.

Responsibilities:

• Define the target data architecture and reusable data foundation
• Identify and structure key data domains and data products
• Design data ownership and governance models
• Establish principles for:
• Data quality and validation
• Data lineage and traceability
• Versioning and auditability
• Ensure a modern lakehouse platform acts as the governed backbone for trusted data
• Enable integration of external calculation and authoring tools where appropriate
• Collaborate across business and IT domains to avoid fragmented point-to-point integrations
• Support the creation of reusable, auditable data products for multiple stakeholders

Required experience !!!!!:

• Strong experience in data architecture and modern data platforms (lakehouse)
• Hands-on knowledge of data governance, data products, and domain-driven data design
• Experience working with manufacturing, product data, or industrial environments
• Understanding of sustainability reporting and/or compliance-driven data requirements
• Ability to work across multiple stakeholders: business, IT, data, and compliance teams
• Experience integrating data across systems such as ERP, PLM, and analytics platforms

Nice to have:

• Experience with sustainability-related domains (e.g. lifecycle assessment, carbon footprint, environmental reporting)
• Experience with compliance-driven data (e.g. chemical, product, EHS)
• Familiarity with emerging requirements such as Digital Product Passport

We are looking for a Computer Vision Engineer with strong experience in deep learning and production computer vision systems.

The role involves developing and bringing computer vision models into production, covering the full lifecycle from training and evaluation to deployment and system integration.

Responsibilities:

• Develop and improve Computer Vision and Machine Learning models
• Design and implement solutions for object detection, classification, segmentation, and tracking
• Work with large-scale image, video, and telemetry datasets
• Prepare, process, and maintain datasets for model training and evaluation
• Manage model training, validation, and testing workflows
• Optimize models for production deployment and real-time performance
• Integrate ML models into software services, applications, and APIs
• Analyze model performance and identify opportunities for quality improvement
• Participate in the design and architecture of AI components within the product ecosystem
• Collaborate closely with Backend, Infrastructure, Data, and Product Engineering teams
• Contribute to the development of MLOps practices and the end-to-end machine learning lifecycle.

Requirements:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience working with thermal imaging data (thermal cameras, infrared imagery) would be an advantage
• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

We are looking for a Computer Vision Engineer with strong experience in deep learning and applied computer vision systems.
The role involves working on challenging CV problems in real-world environments.
We consider Middle and Senior engineers, with scope adapted to experience.
Responsibilities

• Develop, train, and optimize deep learning models for:
  • image retrieval
  • image matching (keypoint detection and matching)
  • auxiliary perception tasks supporting the main pipeline
• Evaluate models using quantitative metrics, including:
  • retrieval quality (mAP, Recall@K)
  • matching performance (precision/recall, repeatability)
  • end-to-end system metrics (accuracy, latency, robustness)
• Optimize models for production deployment using modern toolchains:
  • ONNX / TensorRT / OpenVINO / edge acceleration where applicable
  • model compression techniques (quantization, pruning, distillation)
  • latency, memory, and throughput optimization
• Work with large-scale visual datasets and descriptor-based representations
• Collaborate with engineering teams to integrate models into production systems

Required Qualifications

• 2–4+ years of experience in Computer Vision / Deep Learning
• Hands-on experience with keypoint detection and matching models (e.g. SuperPoint, R2D2, DISK, LightGlue, SuperGlue)
• Experience with image retrieval or metric learning systems
• Strong understanding of geometric and motion-related computer vision concepts:
  • keypoint detection and description
  • image matching and geometric verification (RANSAC, homography, PnP)
  • pose estimation and refinement techniques (PnP, bundle adjustment, pose graph optimization)
  • optical flow and frame-to-frame tracking
  • vector search / ANN methods for descriptor retrieval
• Strong Python skills (PyTorch and scientific computing stack)
• Ability to read and understand inference code in C++

Nice to Have

• Experience with noisy or imperfect real-world datasets
• Self-supervised or unsupervised learning methods (contrastive learning, homography supervision, etc.)
• Experience optimizing models for edge deployment (quantization, pruning, distillation)
• Familiarity with FAISS or similar vector search systems
• Experience with optimization libraries for geometric problems (bundle adjustment, pose refinement)
• Understanding of real-time constraints (latency, memory, CPU inference budgets on ARM or low-power x86 systems)

We are looking for Computer Vision Engineers with strong experience in classical and geometric computer vision, and hands-on experience with SLAM, Visual-Inertial Odometry (VIO), or related localization systems.

We are open to candidates of different seniority levels (Junior to Senior), with responsibilities and scope defined by experience.

Responsibilities:

• Develop and optimize classical and geometric computer vision algorithms
• Work with feature tracking, matching, and geometric processing
• Contribute to SLAM / VIO pipeline components
• Integrate and test multi-sensor fusion systems (camera + IMU)
• Design and run experiments, evaluate algorithm performance
• Translate research papers into practical implementations
• Collaborate with cross-functional engineering teams

Required Qualifications:

• Hands-on experience with classical computer vision
• Understanding of geometric computer vision concepts, including camera models, feature detection, and tracking
• Familiarity with SLAM and/or Visual-Inertial Odometry (VIO) concepts
• Experience with C++ and Linux environments
• Ability to design, implement, and optimize computer vision algorithms in practice
• Ability to learn from and implement research-based methods
• Degree or ongoing studies in Computer Science, Mathematics, Physics, Engineering, or a related STEM field

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems
• Robotics or navigation background

Domain: iGaming / Gambling
Format: Product company
Experience: 5+ years

About the Company

We are an international product company operating in the gambling sector. Our platform delivers real-time personalization for casino and sportsbook products using advanced machine learning. The solution processes live behavioral, transactional, and contextual data to improve player engagement, retention, and overall performance for operators worldwide.

Our focus is on building production-grade ML systems that directly influence what users see in real time — from game recommendations to personalized content and promotions.

Role Overview

We are looking for a Senior Data Scientist to join a product-focused team working on real-time personalization and recommendation systems for iGaming platforms.

This is a hands-on role that combines modeling, experimentation, and close collaboration with engineering and product teams in a high-load, real-time production environment.

Main Responsibilities

• Develop ML-driven features for casino products using supervised learning (regression, ranking, classification)
• Maintain and improve existing recommendation systems in production
• Enhance models using gradient boosting and other supervised approaches
• Perform data cleaning, preprocessing, and feature engineering
• Design and maintain pre- and post-processing workflows
• Optimize training and inference pipelines for performance and reliability
• Integrate ML models into Airflow pipelines in a multi-tenant environment
• Adapt and configure the solution for different clients (tenants)
• Collaborate closely with product and engineering teams on experimentation and feature delivery

As Part of the Team You Will

• Work cross-functionally with data scientists, engineers, product owners, designers, and researchers
• Analyze large-scale datasets to extract insights for product and business decisions
• Propose, implement, and evaluate ML approaches to solve real business problems
• Support and evolve a recommendation solution used across multiple tenants
• Influence product strategy through research, experimentation, and data-driven insights into user behavior

Experience & Education

• 5+ years of professional experience in data science
• Degree in a quantitative field (Mathematics, Statistics, Computer Science, or similar)

Core Skills

• Strong proficiency in Python and SQL
• Hands-on experience with data processing tools (Pandas, Polars)
• Solid engineering skills for building and maintaining scalable ML systems
• Experience implementing observability in ML pipelines (metrics, logging, alerting)
• Knowledge of Docker and Kubernetes
• Strong analytical mindset with the ability to solve loosely defined problems
• Hands-on experience with supervised ML techniques, including:
  • Regression and ranking models (XGBoost, LightGBM, CatBoost, neural networks)
  • Feature engineering and model evaluation (AUC, NDCG, MSE, uplift metrics)
  • Personalization or recommendation systems
• Proven experience deploying ML models to production (near real-time or batch)
• Solid understanding of statistical methods (A/B testing, significance testing)

Nice to Have

• Production experience with large-scale recommendation systems
• Experience with Airflow, Valkey/Redis, FastAPI in production
• Familiarity with contextual bandits or reinforcement learning
• Experience with AutoML tools

Project description

As part of the AI transformation strategy, Kyivstar invests resources in the integration of GenAI/Speech technologies into internal processes and day-to-day tasks, but also uses gained experience to help partners and clients to receive maximum benefits from these technologies too.

One of the key directions of this strategy is the development of AI assistants and services for external partners and clients. To achieve this, company is looking for AI Engineer (Speech) - specialists in the field of GenAI and Speech Processing with deep ML/DL background and practical skills in developing AI assistants and voice bots.

Necessary skills

• 4+ years of experience in ML/DL with strong focus on STT/TTS
• Hands-on experience training and deploying models for various speech processing tasks (e.g., speech classification, speech-to-text, text-to-speech, and speaker diarization)
• Practical experience building AI applications using LLMs
• Strong Python skills with experience in writing scalable software modules
• Fundamental knowledge of  ML/DL theoretical concepts
• Familiarity with RESTful APIs and basic web development principles
• Proficient in version control (Git) and containerization tools (Docker)

Would be a plus

• Experience with real-time / low-latency speech systems
• Experience with distributed data processing and training in multi-node, multi-GPU environments
• Experience with LangChain, LangGraph, and FastAPI
• Experience with Azure/AWS
• Familiarity with PySpark for large-scale data processing
• Exposure to Data Science in the Telecom industry

Responsibilities

• Design, train, and optimize ASR and TTS models for production use
• Design and develop AI-powered assistants
• Fine-tune and optimize large-scale models for specific business needs
• Collaborate with DevOps team to deploy the solution

• Plan and manage ML projects, articulate methodologies, and communicate results and business impact to stakeholders and customers

   

Proposed:

• Working with huge amounts of data at the largest operator in Ukraine
• Hands on experience with Cloud technologies and tools
• Great diversity of tasks and projects to utilize your knowledge and skills; flexibility in tools and approaches
• Opportunity to grow within the team of talented data scientists

Огляд

Вакансія передбачає службу у складі 12-го окремого центру спеціального призначення (Б12). Загін застосовує всі типи безпілотних систем на основних напрямках бойових дій, де постійно розташовані тактичні групи. Це дозволяє добре розуміти фронт та обрати собі безпілотний апарат, який найбільше відповідає вашим талантам та темпераменту. Окрема важлива задача загону — збір та узагальнення передового бойового досвіду для найвищого командування ЗСУ.

Обов’язки

• збір/очищення/підготовка даних (ETL/ELT), робота з великими датасетами
• дослідження даних (EDA), пошук закономірностей, перевірка гіпотез
• побудова та навчання ML-моделей (класифікація/регресія/кластеризація/ранжування/прогнозування часових рядів)
• оцінка якості моделей: метрики, кросвалідація, аналіз помилок, тестування на bias/leakage
• Feature engineering, selection, інтерпретація (SHAP/feature importance)
• впровадження в прод: пайплайни, inference, моніторинг якості/дрейфу, ретренінг
• підготовка звітів/дашбордів, презентація результатів бізнесу
• співпраця з Data Engineering / Backend / Product: постановка задач, вимог до даних, експериментів (A/B)
• документування рішень, відтворюваність (репозиторій, експерименти, версіонування)

Вимоги

• знання Python для DS/ML (pandas, numpy, scikit-learn), основ ООП
• SQL (join, window functions, оптимізація запитів на базовому рівні)
• розуміння статистики: розподіли, довірчі інтервали, тестування гіпотез, кореляція/причинність
• знання базових ML-підходів: bias-variance, overfitting, регуляризація, preprocessing
• досвід з версіонуванням (Git) та відтворюваними експериментами
• уміння пояснювати результати нетехнічній аудиторії

Умови

• мобілізація до кінця воєнного стану або службу за контрактом
• можливість переведення чинних військовослужбовців за згодою безпосереднього командира
• можливість служби для кандидатів, які за висновком ВЛК придатні до служби у військових частинах забезпечення, ТЦК та СП, ВВНЗ, навчальних центрах тощо
• дружній колектив, творча атмосфера

WallPanels.com — американська компанія з офісом у сонячному Маямі, яка спеціалізується на створенні преміальних інтер'єрів та кастомних рішень для клієнтів у США. Ми працюємо в luxury-сегменті, реалізовуючи проєкти з високими бюджетами — від дизайнерських стінових панелей та вбудованих меблів до комплексних рішень для приватних будинків.

Наші клієнти цінують якість, сервіс та індивідуальний підхід, тому ми шукаємо професіоналів, які прагнуть створювати реальні зміни, автоматизувати бізнес-процеси та впроваджувати сучасні AI-рішення.

Ми шукаємо AI Business Automation Specialist, який не просто вміє працювати з AI-інструментами, а бачить бізнес-процеси, знаходить вузькі місця та перетворює рутинні операції на ефективні автоматизації.

Якщо ви любите оптимізувати процеси, швидко розбираєтеся в нових задачах, самостійно пропонуєте рішення та доводите їх до результату — ми будемо раді бачити вас у команді.

Що ви будете створювати

• Аналізувати бізнес-процеси та знаходити можливості для автоматизації.
• Створювати AI-агентів і автоматизовані workflow.
• Інтегрувати CRM, Google Sheets, AI-сервіси та інші бізнес-інструменти.
• Автоматизувати звітність, нагадування, документообіг та внутрішні процеси компанії.

• Розробляти MVP-рішення, тестувати їх та масштабувати після успішного запуску.

   

Над чим ви працюватимете

• AI-агент для контролю CRM та лідів, які залишилися без відповіді.
• Автоматичне заповнення документів і Project Passports.
• AI-саммарі зустрічей із постановкою задач та визначенням відповідальних.
• Автоматичні нагадування співробітникам.
• Операційні та фінансові дашборди.
• Автоматизація estimating та pre-estimate процесів.

• Інтеграція внутрішніх систем між собою для мінімізації ручної роботи.

   

Що ми очікуємо від вас

• Досвід роботи з n8n, Make або Zapier.
• Практичний досвід використання OpenAI, Claude та інших AI-сервісів.
• Розуміння принципів роботи API та Webhooks.
• Досвід інтеграції CRM-систем і Google Sheets.
• Уміння самостійно аналізувати бізнес-завдання та знаходити оптимальні рішення.

• Наявність реальних кейсів автоматизації (портфоліо або опис реалізованих проєктів).

   

Буде перевагою

• Досвід роботи з Bitrix24.
• Базові знання Python або JavaScript.
• Досвід створення Telegram-ботів, Voice Bots та автоматизації документообігу.
• Досвід роботи у сферах construction, sales, operations або project management.

• Базовий рівень англійської мови для роботи з технічною документацією та міжнародними сервісами.

   

Ця вакансія вам не підійде, якщо

• Ви працюєте виключно як ML Engineer або AI Researcher.
• Ви Backend-розробник без досвіду автоматизації бізнес-процесів.
• У вас немає практичних кейсів створення автоматизацій.

• Ви звикли працювати лише за детальними технічними завданнями та не готові самостійно пропонувати рішення.

   

Що ми пропонуємо

• Повністю віддалену роботу.
• Full-time зайнятість.
• Робочий графік, синхронізований із командою в Маямі (Eastern Time).
• Можливість працювати напряму з керівництвом компанії та впливати на розвиток бізнесу.
• Реальні задачі, сучасний стек AI-інструментів і свободу у виборі найкращих технічних рішень.

• Мінімум бюрократії, максимум можливостей реалізовувати власні ідеї.

   

Разом із відгуком, будь ласка, додайте посилання на свої проєкти або коротко опишіть автоматизації, які ви вже реалізували. Нам важливо побачити ваш практичний досвід та підхід до вирішення бізнес-завдань.