Jobs Data Science

We are looking for a hands-on Data Scientist to deliver practical AI and GenAI solutions. This is an execution-driven role focused on data quality, model evaluation, and reliable outputs not on BI or data platforms.

You will work directly on building, testing, and delivering AI/ML and GenAI solutions for real client use cases. The role requires strong practical experience and the ability to turn ideas into production-ready implementations.

Responsibilities

• Build and deliver AI / ML proof-of-concepts
• Prepare data, implement models, and write production-ready code
• Apply LLMs in practice, including: prompting, structured outputs, evaluation, retrieval-augmented generation (RAG)
• Work with messy, real-world customer data
• Collaborate closely with client teams and participate in technical workshops

Requirements

• Strong background in Data Science, Machine Learning, or Statistics
• Hands-on experience building ML pipelines in Python or R(e.g. scikit-learn, pandas, numpy)
• Practical GenAI experience with LLMs, LangChain, Chainlit, and RAG
• Comfortable working with unstructured and imperfect data
• English level B2+

A leading mobile marketing and audience platform, empowers the app ecosystem with cutting-edge solutions in mobile marketing, audience building, and monetization. With integration into over 500,000 monthly active apps and a global reach, the platform leverages first-party data to deliver impactful and scalable advertising solutions.

We’re looking for a highly skilled, independent, and driven Machine Learning Engineer to lead the design and development of our next-generation real-time inference services - the core engine powering algorithmic decision-making at scale. This is a rare opportunity to own the system at the heart of our product, serving billions of daily requests across mobile apps, with tight latency and performance constraints.

You’ll work at the intersection of machine learning, large-scale backend engineering, and business logic, building robust services that blend predictive models with dynamic, engineering logic - all while maintaining extreme performance and reliability requirements.

Description:

• Own and lead the design and development of low-latency Algo inference services handling billions of requests per day.
• Build and scale robust real-time decision-making engines, integrating ML models with business logic under strict SLAs.
• Collaborate closely with DS to deploy models seamlessly and reliably in production.
• Design systems for model versioning, shadowing, and A/B testing at runtime.
• Ensure high availability, scalability, and observability of production systems.
• Continuously optimize latency, throughput, and cost-efficiency using modern tooling and techniques.
• Work independently while interfacing with cross-functional stakeholders from Algo, Infra, Product, Engineering, BA & Business.

Requirements:

• B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related technical discipline.
• 5+ years of experience building high-performance backend or ML inference systems.
• Deep expertise in Python and experience with low-latency APIs and real-time serving frameworks (e.g., FastAPI, Triton Inference Server, TorchServe, BentoML).
• Experience with scalable service architecture, message queues (Kafka, Pub/Sub), and async processing.
• Strong understanding of model deployment practices, online/offline feature parity, and real-time monitoring.
• Experience in cloud environments (AWS, GCP, or OCI) and container orchestration (Kubernetes).
• Experience working with in-memory and NoSQL databases (e.g. Aerospike, Redis, Bigtable) to support ultra-fast data access in production-grade ML services.
• Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry) and best practices for alerting and diagnostics.
• A strong sense of ownership and the ability to drive solutions end-to-end.
• Passion for performance, clean architecture, and impactful systems.

Why join us?

• Lead the mission-critical inference engine that drives our core product.
• Join a high-caliber Algo group solving real-time, large-scale, high-stakes problems.
• Work on systems where every millisecond matters, and every decision drives real value.
• Enjoy a fast-paced, collaborative, and empowered culture with full ownership of your domain.

What we offer:

• Polish public holidays.
• 20 working days per year is Non-Operational Allowance and settled to be used for personal recreation matters and are compensated in full. These days have to be used within the year, with no rollover to the next calendar year.
• Health Insurance.
• Gym Subscription (Multisport).

N-iX is looking for a motivated Data Scientist with strong technical skills and business acumen to help turn millions of potential data points into models and actionable insights that can drive product improvements, make customer acquisition more efficient, improve customer retention rates, and drive operating efficiencies on our production and logistics teams.

Responsibilities: 

• Use your quantitative skill set to tackle projects including time-series forecasting, demand planning and many other exciting projects.
• Work alongside the rest of the analytics and data engineering teams to ensure best data practices and showcase your skill set.
• Collaborate with functional stakeholders to identify areas of opportunity and optimization. 
• Create metrics to continuously evaluate the performance of models and maintain and improve the performance of existing machine learning models.

Requirements: 

• 3+ years of experience in data science
• Master’s Degree or extensive experience in Math, Statistics, Economics, Computer Science, or similar quantitative field.
• Advanced skills in SQL and Python
• Ability to use all your skills to complete your work, we are a small team and everyone wears multiple hats. You’ll need to use your data science, engineering and communication skills to get the job done
• Knowledge of ETL, statistical testing & analysis, experimental design
• Experience with exploratory data analysis and feature tuning
• Experience of developing, training, and evaluating machine learning models such as LightGBM, XGBoost, SVM, K-means, kNN and others
• Experience working with transactional data, customer segmentation, cohort analysis, time series analysis
• Previous experience with version control and continuous integration to a code base.
• Ability to manage cross functional projects with multiple works streams to completion
• Detail oriented, organized, and able to effectively communicate
• Seen as a key business expert and technical leader
• English Upper Intermediate +

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are looking for a  Data Scientist who will work closely with business teams, quickly dive into the domain, identify problems, and build end-to-end ML and analytics solutions - from idea to production.

We are looking for an experienced Data Scientist who will apply statistical and machine learning techniques to generate insights and build predictive models with real business impact. This role supports Pharmaceutical R&D, Manufacturing, and Commercial operations through advanced analytics and data-driven decision-making.

This is a forward-deployed position, meaning you will be embedded directly within business units, working closely with stakeholders to identify problems, rapidly prototype solutions, and scale validated approaches into production. You will operate in a startup-like mode while contributing to enterprise-level platforms and standards.

What you'll do in this role  

• Lead complex data science and machine learning initiatives across multiple teams
• Design, build, and deploy end-to-end ML and analytical solutions, from problem discovery to production
• Apply advanced statistical methods to support data-driven decision-making
• Work with large, complex, and often ambiguous data landscapes, solving integration challenges
• Rapidly prototype, validate hypotheses, and transition solutions into scalable production systems
• Collaborate closely with business stakeholders and influence technical and product roadmaps
• Mentor engineers and data scientists, setting analytical and engineering best practices
• Design and evaluate AI-augmented workflows and ensure responsible AI usage
• Create and maintain high-quality documentation and knowledge-sharing systems

We're looking for

• 8+ years of experience in Data Science, Machine Learning, or Advanced Analytics
• Strong background in statistics, experimentation, and predictive modeling
• Proven experience delivering and operating production-grade ML systems
• Ability to work effectively in ambiguous problem spaces and translate business needs into technical solutions
• Strong communication skills with both technical and non-technical stakeholders
• A business-oriented mindset with a strong sense of ownership and accountability
• Bachelor’s degree in Computer Science, Engineering, or a related field
• Fluent English

How to knock our socks off

• Experience in Pharmaceutical or Life Sciences domains.
• Knowledge of cloud platforms (AWS, GCP, Azure) for ML deployments.
• Familiarity with data governance, regulatory compliance, or GxP standards
• Naming five or more dishes that include beetroot besides borshch 😉

✔ Not checking every box?

This job looks very exciting, but you hesitate to apply because of the confidence gap? Reach out to us anyway! Beetroot is an inclusive workplace that considers all applicants. We’re committed to openness — promoting equality and fostering an environment where different backgrounds, ideas, and experiences are not just accepted, but embraced. So let’s discover together whether we could be an excellent fit for each other.

Please send us your CV in English, and we'll be happy to discuss your application further.

Step into a mission-critical role at the intersection of Generative AI and life-saving technology. We are partnering with a titan of Japanese industry to revolutionize how medical and industrial equipment is managed in hospitals and facilities worldwide. You will be a founding member of a team building a sophisticated GenAI platform designed to provide instant, intelligent access to complex product knowledge—from assembly and configuration to intricate repair procedures. This project is in its infancy, offering you the unique "greenfield" opportunity to act as a primary architect, defining the tech stack and software patterns that will power the next generation of industrial intelligence.

Requirements:

• Extensive experience in Data Science and Machine Learning with a strong focus on Natural Language Processing (NLP) and Data Engineering.
• Proven track record of designing and implementing complex data models for large-scale information retrieval systems.
• Expertise in cleaning and structuring highly unstructured data (e.g., audio transcripts, PDFs, manual reports, and sensor data).
• Good experience with the Azure cloud ecosystem and its data services.
• Hands-on experience implementing Large Language Models (LLMs) and Open AI capabilities within production environments.
• Strong communication skills to work with cross-functional teams and understand the nuances of highly technical documentation.

Nice to Have:

• Ability to define and implement software architecture from scratch for ML-driven platforms.
• Experience in knowledge graph construction or advanced data linking techniques is preferred.
• A background in regulated industries (Healthcare or Industrial) is an advantage.

Job Responsibilities

As a Senior ML Data Scientist, your primary focus will be the transformation of vast, unstructured "tribal knowledge" into a high-fidelity digital brain. You will orchestrate the entire data lifecycle, from the initial ingestion of diverse sources—such as captured expert interviews, technical service manuals, and real-time IoT streams—to the final deployment of GenAI agents. Your work involves designing complex data models that can represent intricate relationships between technical components, cleaning and structuring noisy data, and building the pipelines that link these insights together for OpenAI-driven consumption. You will be responsible for defining the architecture of the end solution on Azure, ensuring that the resulting GenAI agents provide accurate, quick, and context-aware responses to technicians and medical professionals on the front lines.

Project Description:

The primary goal of the project is the modernization, maintenance and development of an eCommerce platform for a big US-based retail company, serving millions of omnichannel customers each week.
Solutions are delivered by several Product Teams focused on different domains - Customer, Loyalty, Search and Browse, Data Integration, Cart.
Current overriding priorities are new brands onboarding, re-architecture, database migrations, migration of microservices to a unified cloud-native solution without any disruption to business.

Responsibilities:

We are looking for an experienced Data Engineer with Machine Learning expertise and good understanding of search engines, to work on the following:
- Design, develop, and optimize semantic and vector-based search solutions leveraging Lucene/Solr and modern embeddings.
- Apply machine learning, deep learning, and natural language processing techniques to improve search relevance and ranking.
- Develop scalable data pipelines and APIs for indexing, retrieval, and model inference.
- Integrate ML models and search capabilities into production systems.
- Evaluate, fine-tune, and monitor search performance metrics.
- Collaborate with software engineers, data engineers, and product teams to translate business needs into technical implementations.
- Stay current with advancements in search technologies, LLMs, and semantic retrieval frameworks.

Mandatory Skills Description:

- 5+ years of experience in Data Science or Machine Learning Engineering, with a focus on Information Retrieval or Semantic Search.
- Strong programming experience in both Java and Python (production-level code, not just prototyping).
- Deep knowledge of Lucene, Apache Solr, or Elasticsearch (indexing, query tuning, analyzers, scoring models).
- Experience with Vector Databases, Embeddings, and Semantic Search techniques.
- Strong understanding of NLP techniques (tokenization, embeddings, transformers, etc.).
- Experience deploying and maintaining ML/search systems in production.
- Solid understanding of software engineering best practices (CI/CD, testing, version control, code review).

Nice-to-Have Skills Description:

- Experience of work in distributed teams, with US customers
- Experience with LLMs, RAG pipelines, and vector retrieval frameworks.
- Knowledge of Spring Boot, FastAPI, or similar backend frameworks.
- Familiarity with Kubernetes, Docker, and cloud platforms (AWS/Azure/GCP).
- Experience with MLOps and model monitoring tools.
- Contributions to open-source search or ML projects.

Languages:

English: B2 Upper Intermediate

Help us push AI further — and faster

LoopMe’s Data Science team builds production AI that powers real-time decisions for campaigns seen by hundreds of millions of people every day. We process billions of data points daily — and we don’t just re-apply old tricks. We design and deploy genuinely novel machine learning systems, from idea to prototype to production.

You’ll join a high-trust team that has a 5-star Glassdoor rating led by Leonard Newnham, where your work moves fast, ships to production, and makes measurable impact.

What you’ll do:

• Design, build, and run large-scale ML pipelines that process terabytes of data
• Apply a mix of supervised learning, custom algorithms, and statistical modelling to real-world problems
• Ship production-grade Python code that’s clear, documented, and tested
• Work in small, agile squads (3–4 people) with DS, ML, and engineering peers
• Partner with product and engineering to take models from idea → production → impact
• Work with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse and more

What you bring:

• Bachelor’s degree in Computer Science, Maths, Engineering, Physics or similar (MSc/PhD a plus)
• 3+ years’ commercial Python experience
• Track record building ML pipelines that handle large-scale data
• Excellent communication skills — comfortable working across time zones
• A curious, scientific mindset — you ask “why?” and prove the answer

Bonus if you have:

• Experience with adtech or real-time bidding
• Agile / Scrum experience
• Knowledge of high-availability infrastructure (ElasticSearch, Kafka, ClickHouse)
• Airflow expertise

About the Data Science Team:

We’re 17 ML engineers, data scientists, and data engineers, distributed across London, Poland, and Ukraine — acting as one team, not a satellite office.

What sets us apart:

• Led by an experienced Chief Data Scientist who codes, leads, and listens
• Inclusive, supportive culture where ideas are heard and people stay
• Strong values: open communication, continual innovation, fair treatment, and high standards
• Track record of publishing award-winning research in automated bidding

Don’t just take our word for it — check our Glassdoor reviews (search “Data Scientist”) for a real view of the culture.

About LoopMe:

LoopMe was founded to close the loop on brand advertising. Our platform combines AI, mobile data, and attribution to deliver measurable brand outcomes — from purchase intent to foot traffic. Founded in 2012, we now have offices in New York, London, Chicago, LA, Dnipro, Singapore, Beijing, Dubai and more.

What we offer:

• Competitive salary + bonus
• Billions of real-world data points to work with daily
• Flexible remote/hybrid options
• Learning budget and career growth support
• Friendly, transparent culture with strong leadership

Hiring process:

1. Intro with Talent Partner
2. 30-min technical interview with Chief Data Scientist
3. Panel with 2 team members (technical, culture & collaboration)
4. Offer – usually within 48 hours of final round

Are you ready to design and deploy AI systems that run at truly massive scale?

We are looking for an experienced Data Scientist for a full-time job to join our team.


Requirements:
- 2+ years of experience as a data scientist
- BSc in Mathematics, Statistics, Computer Science, Economics, or another related field.
- Experience in using Python & SQL
- Experience with Airflow and GCP
- Experience with Git & CI/CD
- Upper Intermediate English — written and spoken
- Ability to design creative solutions for complex requirements
- Ability to learn and lead projects independently, and to work with minimal supervision with customers (tech & business)

Responsibilities:
- Conduct independent research, including defining research problems, creating research plans, designing experiments, developing algorithms, implementing code, and performing comprehensive comparisons against existing benchmarks;
- Clearly communicate your research findings to both technical and non-technical audiences
- Work on various data sources and apply sophisticated feature engineering capabilities
- Bring and use business knowledge
- Build and manage technical relationships with customers and partners.

We offer:
- remote time job, B2B contract
- 12 sick leaves and 18 paid vacation business days per year
- Comfortable work conditions (including MacBook Pro and Dell monitor on each workplace)
- Smart environment
- Interesting projects from renowned clients
- Flexible work schedule
- Competitive salary according to the qualifications
- Guaranteed full workload during the term of the contract
 

We are looking for a full-time Middle Data Scientist / ML Engineer to join our team and take ownership of data-driven components in new products we are building from scratch.
 One of the first phases involves creating a data model of an industrial facility (digital twin) based on historical sensor and operational data, and developing predictive algorithms on top of it. The solution will include a data pipeline, a lightweight system model, forecasting modules, and integration with a simple dashboard.
This is a role for a specialist who communicates clearly, understands data deeply, and can work independently.

Responsibilities
 

• Analyse real industrial datasets and define structure, schemas and preprocessing logic.
• Build data pipelines and prepare clean datasets for modelling.
• Develop interpretable ML/time-series forecasting models.
• Participate in designing a simplified system model (data-driven “digital twin”).
• Prepare models for inference and assist with integration into backend services.
• Collaborate closely with PM and other team members, clarify requirements, and communicate modelling decisions.
• Produce clear, concise documentation for data and models.

Requirements
 

• 3+ years of experience as a Data Scientist or ML Engineer.
• Strong Python skills (pandas, scikit-learn; PyTorch/TensorFlow).
• Experience with time-series modelling or forecasting.
• Solid understanding of data cleaning, feature engineering and evaluation.
• Ability to work independently and take ownership of tasks without supervision.
• Good communication skills and ability to work with evolving or partially defined requirements.
• Experience with Docker and backend integration is a plus.

Nice to Have
 

• Experience with industrial or IoT data
• Experience with FastAPI or simple dashboards
• Understanding of model deployment workflows

About us
 

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers,

with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production,

agricultural business, parcel delivery, logistics and banking. 

Since its inception in 1997, Fozzy Group has focused on making innovative business improvements, creating

new opportunities for the market and further developing the industry as a whole.
 

Job Description:
 

The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast[1]growing food delivery business. In this role, you will focus on time series forecasting, regression modeling,

simulation modeling, and end-to-end machine learning pipelines to support resource planning and

operational decision-making.

You will be responsible for developing simulation-based models that serve as a foundation for a digital twin

of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity

planning and operational optimization.

You will work closely with product, engineering, and operations teams to transform data into measurable

business impact through production-ready ML and simulation solutions.
 

Job Responsibilities
 

• Develop and implement time series forecasting models for resource planning (demand, capacity,

couriers, delivery slots, operational load);

• Build regression and machine learning models to explain key drivers and support operational

decisions;

• Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and

ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);

• Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in

production using AWS SageMaker;

• Orchestrate training and inference workflows with Apache Airflow;

• Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable

recommendations;

• Collaborate with product managers, engineers, and operations teams to define business problems

and validate analytical solutions;

• Monitor model performance, forecast stability, and business impact over time.
 

Requirements
 

• Bachelor’s Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics /

Econometrics;

• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;

• At least 2 years working experience on Data Science;

• Experience of the full cycle of model implementation (data collection, model training and evaluation,

model deployment and monitoring);

• Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
 

Skills

Must Have
 

• Strong proficiency in Python with solid application of object-oriented programming (OOP) principles

(modular design, reusable components, maintainable code);

• Solid experience in time series forecasting and regression modeling;

• Practical knowledge of:

o Classical and ML forecasting techniques;

o Statistical methods (hypothesis testing, confidence intervals, A/B testing);

• Advanced SQL skills (window functions, complex queries);

• Experience building automated ML pipelines;

• Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
 

Preferred
 

• Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);

• Experience with Apache Airflow for data and ML workflow orchestration;

• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);

• Experience working with large-scale production data systems.
 

What We Offer
 

• Competitive salary;

• Professional & personal development opportunities;

• Being part of dynamic team of young & ambitious professionals;

• Corporate discounts for sport clubs and language courses;

• Medical insurance package

We are looking for you!

We are seeking a Senior Data Scientist to drive the next generation of data-driven solutions. This role calls for deep expertise in data architecture, advanced analytics, and pipeline design. If you are a seasoned professional ready to lead initiatives, innovate with cutting-edge techniques, and deliver impactful data solutions, we’d be excited to have you join our journey.

Contract type: Gig contract
 

Skills and experience you can bring to this role

Qualifications & experience:

• At least 3 years of commercial experience with Python, Data Stack (NumPy, Pandas, scikit-learn) and web stack (Fast API / Flask / Django);
• Familiarity with one or more machine learning frameworks (XGBoost, TensorFlow, PyTorch);
• Strong mathematical and statistical skills;
• Good Understanding of SQL/RDBMS and familiarity with data warehouses (BigQuery, Snowflake, Redshift, etc.);
• Experience building ETL data pipelines (Airflow, Prefect, Dagster, etc);
• Knowledge of Amazon Web Services (AWS) ecosystem (S3, Glue, Athena);
• Experience with at least one MMM or marketing analytics framework (e.g., Robyn, PyMC Merydian or similar);
• Strong communication skills to explain technical insights to non-technical stakeholders.

Nice to have:

• Knowledge of digital advertising platforms (Google Ads, DV360, Meta, Amazon, etc.) and campaign performance metrics;
• Exposure to clean rooms (Google Ads Data Hub, Amazon Marketing Cloud);
• Familiarity with industry and syndicated data sources (Nielsen, Kantar etc);
• Experience with optimisation techniques (budget allocation, constrained optimisation);
• Familiarity with gen AI (ChatGPT APIs/agents, prompt engineering, RAG, vector databases). 

Educational requirements:

• Bachelor’s degree in Computer Science, Information Systems, or a related discipline is preferred. A Master's degree or higher is a distinct advantage.

What impact you’ll make 

• Build and validate marketing measurement models (e.g., MMM, attribution) to understand the impact of media spend on business outcomes;
• Develop and maintain data pipelines and transformations to prepare campaign, performance, and contextual data for modelling;
• Run exploratory analyses to uncover trends, correlations, and drivers of campaign performance;
• Support the design of budget optimisation and scenario planning tools;
• Collaborate with engineers, analysts, and planners to operationalise models into workflows and dashboards;
• Translate model outputs into clear, actionable recommendations for client and internal teams.

What you’ll get 

Regardless of your position or role, we have a wide array of benefits in place, including flexible working (hybrid/remote models) and generous time off policies (unlimited vacations, sick and parental leaves) to make it easier for all people to thrive and succeed at Star. On top of that, we offer an extensive reward and compensation package, intellectually and creatively stimulating space, health insurance and unique travel opportunities.

Your holistic well-being is central at Star. You'll join a warm and vibrant multinational environment filled with impactful projects, career development opportunities, mentorship and training programs, fun sports activities, workshops, networking and outdoor meet-ups.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the Role:
We’re looking for a mid-level AI Engineer to help test, deploy, and integrate cutting-edge generative AI models into production experiences centered around human avatars and 3D content. You’ll work directly with the CEO to turn R&D prototypes into stable, scalable products.

Responsibilities:
- Experiment with and evaluate generative models for:

• Human avatar creation and animation;
• 3D reconstruction and modeling;
• Gaussian splatting–based pipelines;
• Generalized NeRF (Neural Radiance Fields) techniques.

- Turn research code and models into production-ready services (APIs, microservices, or batch pipelines).
- Build and maintain Python-based tooling for data preprocessing, training, evaluation, and inference.
- Design and optimize cloud-based deployment workflows (e.g., containers, GPUs, inference endpoints, job queues).
- Integrate models into user-facing applications in collaboration with product, design, and frontend teams.
- Monitor model performance, reliability, and cost; propose and implement improvements.
- Stay up-to-date on relevant research and help prioritize which techniques to test and adopt.

Required Qualifications:
- 3–5+ years of experience as an ML/AI Engineer or similar role.
- Strong Python skills and experience with one or more deep learning frameworks (PyTorch preferred).
- Hands-on experience with deploying ML models to cloud environments (AWS, GCP, Azure, or similar) including containers (Docker) and basic CI/CD workflows.
- Familiarity with 3D data formats and pipelines (meshes, point clouds, volumetric representations, etc.).
- Practical exposure to one or more of the following (professional or serious personal projects):

• NeRFs or NeRF-like methods;
• Gaussian splatting / 3D Gaussian fields;
• Avatar generation / face-body reconstruction / pose estimation;
• Comfort working in an iterative, fast-paced environment directly with leadership (reporting to CEO).

Nice-to-Haves:
- Experience with real-time rendering pipelines (e.g., Unity, Unreal, WebGL) or GPU programming (CUDA).
- Experience optimizing inference performance and cost (model distillation, quantization, batching)
- Background in computer vision, graphics, or related fields (academic or industry).

Job Description

4+ years of experience in computer vision or related fields.
Strong knowledge of machine learning/deep learning.
Hands-on experience with object detectors, instance segmentation, keypoint/pose detection, RNNs/Transformers (computer vision in time domain), tracking algorithms.
Proficiency in programming languages such as Python and C++ (optional).
Extensive experience with computer vision libraries and frameworks like PyTorch, and OpenCV.
Familiarity with image processing techniques and annotation tools.
Experience with hardware integration for vision-based systems.
Good understanding of best practices of software development (code reviews, TDD, Git, etc.)
Advanced English (written and verbal) for daily communication with the customer.
Efficiency in remote development on Linux (VMs, on-premise machines).
Would be a Plus:
Understanding of real-time processing and optimization.
Experience with edge AI deployment.
Experience with optimization and inference libraries (ONNX, TensorRT, OpenVINO, etc.).
Linux development.
Experience in medical computer vision.
Experience in managing huge volumes of visual data.
Ability to leverage advanced nVidia ADA GPU features to speedup training and inference.
Experience with CPU and GPU profiling (nVidia nsight, cProfile)

Job Responsibilities

Contribute to the design, development, code review, and testing of computer vision algorithms and systems.
Develop new features and improve existing functionality in vision-based projects.
Work on the integration of computer vision solutions with third-party tools and hardware.
Collaborate with cross-functional teams to deliver high-quality, compliant products.
Stay updated with the latest advancements in computer vision and machine learning technologies.

Department/Project Description

As a Computer Vision Engineer, you will join a mature and senior team dedicated to developing cutting-edge computer vision solutions for medical applications. Our projects range from advanced image processing to real-time vision systems, contributing to fields like medical devices, robotics, autonomous vehicles and others. We emphasize technical excellence and offer a stimulating environment that encourages innovation and professional growth.

We’re hiring: Data Scientist / ML Engineer
Product: E-commerce solution with AI integration
Format: Remote

What you’ll do

• Build and improve ML models (risk/anomaly-style scenarios)
• Analyze patterns, validate hypotheses, and iterate on models
• Support deployment and monitoring in collaboration with engineering/product

Requirements

• 3+ years of experience
• Hands-on ML/DS workflow experience (data prep, modeling, evaluation)
• Ability to work with production data and deliver measurable outcomes.

What we offer

• 24 paid vacation days/year (after probation)
• Paid sick leave (after probation)
• Remote work option
• Company-supported English courses

About Tie

Tie is building the next generation of identity resolution and marketing intelligence. Our platform connects hundreds of millions of consumers across devices, browsers, and channels—without relying on cookies—to power higher deliverability, smarter targeting, and measurable revenue lift for modern marketing teams.

At Tie, AI is not a feature—it is a core execution advantage. We operate large-scale identity graphs, real-time scoring systems, and production ML pipelines that directly impact revenue, deliverability, and customer growth.

The Role

We are looking for a Senior AI / Machine Learning Engineer to design, build, and deploy production ML systems that sit at the heart of our identity graph and scoring platform. You will work at the intersection of machine learning, graph data, and real-time systems, owning models end to end—from feature engineering and training through deployment, monitoring, and iteration.

This role is highly hands-on and impact-driven. You will help define Tie’s ML architecture, ship models that operate at sub-second latency, and partner closely with platform engineering to ensure our AI systems scale reliably.

What You’ll Do

• Design and deploy production-grade ML models for identity resolution, propensity scoring, deliverability, and personalization
• Build and maintain feature pipelines across batch and real-time systems (BigQuery, streaming events, graph-derived features)
• Develop and optimize classification models (e.g., XGBoost, logistic regression) with strong handling of class imbalance and noisy labels
• Integrate ML models directly with graph databases to support real-time inference and identity scoring
• Own model lifecycle concerns: evaluation, monitoring, drift detection, retraining, and performance reporting
• Partner with engineering to expose models via low-latency APIs and scalable services
• Contribute to GPU-accelerated and large-scale data processing efforts as we push graph computation from hours to minutes
• Help shape ML best practices, tooling, and standards across the team

What You’ll Bring

Required Qualifications

• 5+ years of experience building and deploying machine learning systems in production
• Strong proficiency in Python for ML, data processing, and model serving
• Hands-on experience with feature engineering, model training, and evaluation for real-world datasets
• Ability to travel outside of Ukraine is a must
• Experience deploying ML models via APIs or services (e.g., FastAPI, containers, Kubernetes)
• Solid understanding of data modeling, SQL, and analytical workflows
• Experience working in a cloud environment (GCP, AWS, or equivalent)
• Experience with graph data, graph databases, or graph-based ML

• Familiarity with Neo4j, Cypher, or graph algorithms (community detection, entity resolution)

  Preferred / Bonus Experience

• Experience with XGBoost, tree-based models, or similar classical ML approaches
• Exposure to real-time or streaming systems (Kafka, Pub/Sub, event-driven architectures)
• Experience with MLOps tooling and practices (CI/CD for ML, monitoring, retraining pipelines)
• GPU or large-scale data processing experience (e.g., RAPIDS, CUDA, Spark, or similar)
• Domain experience in identity resolution, marketing technology, or email deliverability

Our Technology Stack

• ML & Data: Python, Pandas, Scikit-learn, XGBoost
• Graphs: Neo4j (Enterprise, GDS)
• Cloud: Google Cloud Platform (BigQuery, Vertex AI, Cloud Run, Pub/Sub)
• Infrastructure: Docker, Kubernetes, GitHub Actions
• APIs: FastAPI, REST-based inference services

What We Offer

• Competitive compensation, including salary, equity, and performance incentives
• Opportunity to work on core AI systems that directly impact revenue and product differentiation
• High ownership and autonomy in a senior, hands-on role
• Remote-first culture with a strong engineering and data focus
• Exposure to cutting-edge problems in identity resolution, graph ML, and real-time AI systems

• Clear growth path toward Staff / Principal IC roles

  What else:

• 4 weeks of paid vacation per year (flexible scheduling)
• Unlimited sick leave — we trust your judgment and care about your health
• US Bank Holidays off (American calendar)
• Remote-first culture and flexible working hours
• Flat structure, no micromanagement, and full ownership

• Opportunity to make a real impact during a critical growth phase

  Interview Process

• Recruitment Screening Call
• Initial call with Head of Data Science & AI and CTO  (30 min) in English
• Technical deep dive Interview (1,5h)  in English

• Optional test-task (paid)

  Why Join Us?

• High-impact delivery leadership role during a critical period
• Real ownership and autonomy
• Opportunity to shape delivery across the entire engineering organization
• Exposure to SaaS, data, integrations, automation, and platform work
• Collaboration with global teams and vendors
• A strong product with real scale and momentum

Why This Role Matters

At Tie, your work will not live in notebooks or experiments—it will power production systems used by real customers at scale. You will help define how AI is embedded into the company’s core platform and play a key role in making machine learning a durable competitive advantage.