Jobs Data Science

Eleven — рекрутингова агенція, яка спеціалізується на пошуку працівників для компаній у галузі військових технологій. Наша мета — підтримувати розвиток оборонної промисловості та допомагати об’єднувати тих, хто наближає до перемоги.

Роботодавець — українська компанія, яка займаємось виробництвом компонентів електроніки від ідеї до втілення! Компанія пропонує можливість реалізувати рішення та впливати на події уже зараз.

У зв’язку з активним розширенням шукаємо в команду Data Annotator.

Обов’язки:

• Анотація та розмітка зображень і відео для задач Computer Vision та Machine Learning;
• Виконання різних типів розмітки: bounding boxes, polygons, keypoints, segmentation masks, classification;
• Робота з інструментами для анотації даних (CVAT, LabelImg, Label Studio, Supervisely або аналоги);
• Підготовка, перевірка та підтримка якості датасетів відповідно до вимог проєкту;
• Дотримання стандартів форматів даних (JSON, XML, COCO, YOLO, Pascal VOC);
• Виявлення та виправлення помилок у розмітці, участь у процесах контролю якості;
• Робота з великими обсягами даних у команді, уточнення вимог до розмітки;
• Дотримання внутрішніх інструкцій, гайдів і дедлайнів.

Вимоги:

• Середня спеціальна або вища освіта;
• Досвід роботи з анотацією даних або підготовкою датасетів буде перевагою;
• Впевнене користування ПК (Windows/Linux);
• Досвід роботи з інструментами для анотації даних (CVAT, LabelImg, Label Studio, Supervisely або аналоги);
• Розуміння основних типів розмітки (bounding boxes, polygons, segmentation тощо);
• Базові знання форматів даних (JSON, XML, COCO, YOLO, Pascal VOC);
• Уважність до деталей, висока якість і швидкість виконання задач;
• Базове розуміння Computer Vision та Machine Learning буде плюсом.

Буде плюсом:

• Досвід роботи з даними з дронів, камер спостереження або інших сенсорів;
• Розуміння специфіки технічних або військових об’єктів у даних;
• Досвід керування дроном (реальним або в симуляторі);
• Наявність водійських прав.

Що ми пропонуємо:

📍 Мінімум бюрократії — короткий шлях від ідеї до її реалізації.

📍Ефективні рішення не відкладаються, а впроваджуються.

📍Швидке професійне зростання у сфері defense-tech.

📍Сучасна техніка для комфортної і продуктивної роботи.

📍Комфортний офіс зі снеками та фруктами, а також паркомісця для співробітників (робота full-time в офісі)

📍Медичне страхування.

📍Оплачувана відпустка та лікарняні.

📍Гнучкий графік роботи ( 8:00-17:00/ 9:00-18:00/ 10:00-19:00/11:00-20:00)

📍Бронювання з першого робочого дня (відповідно до законодавства, за наявності необхідних документів).

We are looking for a Computer Vision / C++ Engineer to join our team and work on real-world computer vision systems.

Responsibilities:
 

- Develop and maintain computer vision solutions in C++;

- Work with geometric computer vision (projective and epipolar geometry);

- Implement classical CV algorithms (demosaicing, tracking, optical flow, color calibration, image enhancement);

- Fine-tune existing deep learning models (e.g. YOLO) and train custom models using PyTorch;

- Deploy DL models in C++ using inference runtimes (ONNX Runtime, OpenCV DNN or similar);

- Implement model output decoding and post-processing;

- Develop camera-related software;

- Write efficient multi-threaded code.

Requirements:
 

- Strong C++ skills;

- Solid background in computer vision;

- Practical experience with deep learning for CV and PyTorch;

- Experience with deploying models to C++ applications and inference runtimes;

-Experience with multi-threaded programming and camera systems.

Overview
We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied machine learning and data engineering, ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences;
• Stay up to date with recent ML/AI advancements and evaluate promising methods for future implementation.

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

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
• Test task in Hackerrank for 1h
• Technical deep dive Interview (1,5h)  in English

• Final interview with CTO in English

  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.

About the Role

We are seeking a highly skilled and mission-driven Data Scientist to join our customer team and lead the development of our Patient Risk Scoring machine learning initiatives. In this role, you will build predictive models that identify high-risk patients for interventions, ultimately improving patient outcomes and optimizing care delivery. You will leverage Microsoft Fabric to manage end-to-end machine learning workflows, drawing insights from Electronic Health Record (EHR) data sources. If you are passionate about the intersection of advanced artificial intelligence and healthcare innovation, we want to hear you.

Responsibilities

• Model Development & Deployment: Design, train, evaluate, and deploy machine learning models to predict patient risk scores (e.g., medication refusal, non-compliance, decompensation etc.).
• EHR Data Engineering & Processing: Extract, clean, and transform healthcare data from EHR systems (e.g., Credible) to build robust feature sets for predictive modeling.
• End-to-End Analytics with Microsoft Fabric: Utilize Microsoft Fabric’s unified analytics platform (including Data Engineering, Data Science, and Real-Time Analytics workloads) to orchestrate data pipelines, manage Lakehouse architectures, and scale ML training/inference.
• Clinical Collaboration: Partner closely with clinical stakeholders, medical officers, and care teams to define risk cohorts, ensure the clinical validity of model features, and translate model outputs into actionable clinical workflows.
• MLOps & Monitoring: Establish continuous integration, deployment, and monitoring of ML models to track data drift, model degradation, and fairness/bias over time.
• Compliance & Privacy: Ensure all data handling and modeling practices strictly adhere to healthcare regulations (e.g., HIPAA, HITRUST) and maintain the highest standards of data security and patient privacy.

Qualifications

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Bioinformatics, Health Informatics, or a related quantitative field.
• Professional Experience: 4+ years of experience developing and deploying machine learning solutions in production environments, preferably within healthcare or clinical data ecosystems.
• Microsoft Fabric Experience: Hands-on experience building and deploying data and ML workflows within the Microsoft Fabric ecosystem (OneLake, Notebooks, Spark, Data Factory).
• Machine Learning Proficiency: Strong grasp of classical machine learning algorithms (e.g., XGBoost, Random Forests, Logistic Regression) and modern deep learning techniques, specifically for tabular and time-series data.
• Programming Skills: Advanced proficiency in Python and SQL. Experience with data manipulation and ML libraries (Pandas, PySpark, Scikit-Learn, PyTorch, or TensorFlow).
• Communication: Excellent ability to translate complex technical and statistical concepts to non-technical clinical and business stakeholders.

Nice to Have

• Cloud Certifications: Relevant Microsoft Azure or Fabric certifications.

Work Environment & Collaboration

• Full-time: 8 hours a day.
• Schedule: Mon – Fri 9-5 (US EST) overlap with team at least 4 hours.
• Team Structure: Work independently on assigned tasks with support from experienced team members.
• Communication: Primarily asynchronous via email and MS Teams.

We are looking for an AI/ML Engineer to build and scale AI-powered solutions for real-world use cases. This is a hands-on role focused on developing agentic systems, RAG pipelines and production-grade LLM integrations.

Requirements

• 4+ years of commercial development experience 
• Strong experience with LLM-based systems (RAG, agents, tools)
• Ability to design end-to-end AI architecture (data → retrieval → response)
• Experience with evaluation pipelines (golden datasets, metrics, LLM-as-judge)
• Solid understanding of prompt engineering and iteration
• Experience working with databases (Postgres) + vector search
• Understanding of data processing, PII detection, and safe data handling
• Familiarity with fine-tuning approaches (LoRA/QLoRA) and when to use them
• Ability to review and validate AI-generated code
• Strong engineering mindset (scalability, reliability, structured thinking)

Responsibilities

• Build AI-powered features using LLMs (Claude, OpenAI, etc.)
• Develop and optimize RAG pipelines
• Create AI agents and autonomous workflows
• Fine-tune and adapt ML/LLM models for specific use cases
• Integrate AI solutions into products via APIs
• Collaborate with the team and clients to deliver production-ready solutions

We offer

• Flexible working hours
• 20 working days paid vacation and 15 sick leaves
• Fully paid medical insurance
• English classes in the office
• No time trackers — ability to do quality work
• Friendly team and enjoyable working environment