Jobs Data Scientist

Our Client is a cybersecurity software company that specializes in network and cloud security policy management and automation. It's platform helps large enterprises visualize, automate, and enforce consistent security policies across complex hybrid environments — including firewalls, cloud services, SASE, SD-WAN, and microsegmentation — while ensuring compliance and reducing risk.

Position Description:

This role combines excellent technical skills, driving multidisciplinary Data Science initiatives within complex, security policy management systems. The role drives the development of innovative, production-grade AI capabilities - including security AI agents and advanced machine learning models built on complex security data. Original thinking, deep technical rigor, intellectual agility, and exceptional problem-solving are essential.

Key Responsibilities

• Develop Data Science initiatives from problem definition through validation, production deployment, and monitoring of AI systems
• Develop security-focused AI agents and reasoning systems
• Develop advanced ML capabilities, including predictive modeling, anomaly detection, and classification
• Adapt and fine-tune LLM technologies for domain-specific security use cases

Position Requirements:

• M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline
• At least 3 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
• Deep understanding of machine learning theory and practical model behavior
• Expertise in Python and the modern Data Science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch / TensorFlow, etc.)
• Solid understanding of LLM architectures and fine-tuning methodologies
• Excellent interpersonal skills and proven ability to work within multidisciplinary product teams
• Strong analytical rigor and structured problem-solving capability

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 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 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++

Project

The project focuses on a deep refactoring and optimization of the reporting ecosystem combining Salesforce CRM and Tableau. The main goal is to redesign current data flows, replacing the bulky and slow architecture with a modular system of reusable components. You will work on a process redesign to ensure speed, data accuracy, and ease of future system maintenance.

Responsibilities

• Development and Redesign: designing and supporting complex interactive visualizations in Tableau Desktop with a focus on modularity.
• Architecture Optimization: transforming bulky data flows into a fast and stable reporting system.
• Integration and Setup: working with data streams from Salesforce CRM and ERP systems (SAP, Odoo, MS Business Central).
• Technical Optimization: performance tuning (Data Extracts, calculated fields, SQL query optimization).
• Business Collaboration: gathering requirements from stakeholders and translating them into clear technical specifications for visualization.
• Data Governance: ensuring data accuracy, integrity, and security (including Row-Level Security).

Requirements

• Must-have:
  • 1.5-2+ years of commercial experience with Tableau (Desktop, Server/Cloud) or other BI tools.
  • Strong SQL skills (writing complex queries, joins, CTEs).
  • Understanding of CRM and ERP system architecture (how data is stored and interconnected).
  • Intermediate+ English level (for technical communication and documentation).
• Nice-to-have:
  • Experience with Tableau and Salesforce integration (a significant plus).
  • Experience with Tableau Prep or other ETL tools (Alteryx, KNIME).
  • Tableau Desktop Specialist or Certified Data Analyst certification.
  • Experience with cloud data warehouses (Snowflake, BigQuery, AWS Redshift).

Conditions

• Collaboration Type: Part-time (Freelancer / Contract).
• Location: Remote.
• Schedule: Flexible (details to be discussed based on your availability).

Selection Process

1. Recruiter screening.
2. Technical interview with the Tech Lead.
3. Offer.

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

Data Scientist – Computer Vision 

About Cyberette 
Cyberette is an AI-native cybersecurity startup developing forensic-grade technology to detect digital manipulation across video, audio, and images. Our mission is to restore trust in digital communication and protect people, organizations, and institutions from deception in the AI era. 

About the Role 
We are looking for a Computer Vision Data Scientist with strong initiative and technical excellence to join our core development team. You’ll be responsible for designing, training, and optimizing computer vision models and architectures used in our deepfake detection and forensic analysis platform. 

This role requires someone who thrives in fast-paced environments, loves solving complex problems, and brings both creativity and rigor to their work. You’ll collaborate closely with our founders and engineers to push the limits of multimodal AI for real-world impact. 

Key Responsibilities 

• Develop, train, and deploy computer vision models for image and video manipulation detection. 
• Research and experiment with new architectures, model ensembles, and multimodal fusion techniques. 
• Preprocess, clean, and manage large-scale datasets for training and evaluation. 
• Optimize model accuracy, latency, and scalability for enterprise-grade performance. 
• Contribute to the design of the model evaluation framework and internal benchmarking tools. 
• Collaborate with other engineers and researchers to integrate models into production pipelines. 
• Document methodologies, experiments, and findings clearly and systematically. 

Requirements 

• MSc/PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field. 
• Strong experience in computer vision (CNNs, Transformers, multimodal models). 
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).  
• Solid understanding of ML ops, dataset curation, and model evaluation.  
• Proven experience building and training models from scratch.  
• Excellent analytical and problem-solving skills.  
• Self-driven, disciplined, and collaborative mindset.  

What We Value 
At Cyberette, we believe technology should serve people. We are a team of builders united by a shared sense of purpose — creating tools that make the digital world safer and more truthful. If you care deeply about impactful innovation and want your work to matter, you’ll feel at home here. Neurodivergent friendly. 

Bonus Skills 

• Experience with audio or multimodal analysis. 
• Knowledge of adversarial attacks or deepfake generation methods. 
• Experience in real-time inference or edge deployment. 

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Join us as a Data Architect / Lead and play a key role in shaping the data foundation behind our next generation of analytics and AI solutions. In this position, you’ll define the architecture vision for our modern data ecosystem, guide a growing team of Data Engineers, and build cloud‑native platforms that unlock enterprise‑wide insights. This is a high‑impact role where you’ll work closely with business and technology leaders, influence strategic decisions, and drive the adoption of advanced analytics and Generative AI across the organization.

What You’ll Do:

Lead & Strategize

• Lead and mentor Data Engineers, fostering innovation and continuous improvement.
• Own the data architecture vision aligned with business goals.
• Partner with executives and stakeholders to turn strategic needs into scalable data solutions.

Architect & Build

• Design and optimize modern data platforms using Azure Data Lake, Databricks, SQL Server, Microsoft Fabric, and NoSQL.
• Build robust, scalable data pipelines across diverse data sources.
• Implement strong data quality, governance, and security practices.
• Support advanced analytics, machine learning, and AI-based solutions.

Enable Insights

• Build solutions that deliver accurate, timely insights for decision-makers.
• Collaborate on Power BI dashboards and executive reporting.
• Integrate Generative AI into insight-generation workflows.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 4+ years in data engineering, architecture, or analytics roles.
• Experience leading Data Engineering teams in enterprise settings will be a plus.
• Strong skills in Azure data services, Databricks, SQL, NoSQL, and Microsoft Fabric.
• Hands-on Power BI and enterprise reporting experience.
• Proven ability to build data pipelines and enforce data quality.
• Excellent communication skills, especially with executive stakeholders.
• Relevant certifications (Azure Data Engineer, Databricks, Fabric Analytics, etc.) are a plus.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.

Responsibilities: 

• Implement and optimize low-level computer vision algorithms under guidance
• Contribute to modules related to feature extraction, tracking, matching, and geometric processing
• Assist in the integration and testing of SLAM/VIO components
• Perform experiments, analyze results, and help prepare reports
• Work closely with senior engineers to explore and apply recent CV research.

Required Qualifications:

• 1+ years of hands-on experience with classical computer vision
• Basic understanding of geometric computer vision principles
• Experience implementing low-level CV algorithms (e.g., filtering, feature detection, camera models)
• Familiarity with SLAM or VIO concepts
• Working knowledge of C++ and Linux
• Ability to learn quickly and navigate recent CV researc
• Degree or ongoing studies in a 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

We're seeking an exceptional Data Architect to lead data storage strategy and design across our multi-product SaaS platform as we unify independent products into a coherent platform. This role combines strategic leadership with hands-on technical expertise—you'll shape our data architecture vision while getting into the details during implementation and troubleshooting.
 

Key Responsibilities: 
•⁠  ⁠Drive data architecture unification across multiple SaaS products, creating coherent patterns while respecting product needs.
•⁠  ⁠Partner with vertical technical leads to provide horizontal architectural support and alignment.
•⁠  ⁠Design and optimize data storage across multiple technologies—AWS OpenSearch/Elasticsearch, relational databases, S3, NoSQL, and data warehousing.
•⁠  ⁠Optimize for performance and resilience— indexing, querying, high availability, redundancy, and disaster recovery at scale.
•⁠  ⁠Support AI initiatives—partner with our AI specialist team on data architecture for AI capabilities.
•⁠  ⁠Bring clarity from ambiguity—translate complex challenges into clear architectural direction.
•⁠  ⁠Build capability, not dependencies—mentor engineers so teams become more self-sufficient.
•⁠  ⁠Balance performance, cost, and reliability across our platform.

Qualifications:
•⁠  ⁠Deep expertise in AWS OpenSearch/Elasticsearch—you've solved hard problems at scale with indexing, querying, and performance.
•⁠  ⁠Broad data technology experience—relational databases (e.g. PostgreSQL, MySQL, RDS), object storage (S3), NoSQL (e.g. DynamoDB, MongoDB, Redis), data warehousing.
•⁠  ⁠Cloud and container knowledge—AWS preferred (Azure/GCP also valued); understand stateful services in Kubernetes.
•⁠  ⁠Proven platform architecture experience—track record of driving technical strategy across multiple teams or products at scale.
•⁠  ⁠Senior-level maturity—you make those around you better through mentorship and capability building.
•⁠  ⁠Influence without authority—you work effectively across teams, bring clarity from ambiguity, and think strategically.
•⁠  ⁠SaaS experience—comfortable with multi-tenant environments and operational excellence.

Location: EU or Ukraine
Type: Fulltime 
Start: ASAP

About The Role

As a Senior/Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work
• Upper-intermediate English proficiency (B2 or higher).
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

Why Join Us?

• High-Impact Data — Work with vast datasets generated by over a million daily visits, uncovering valuable insights.
• Collaborative Analytics Team — Join a team of 30+ skilled analysts who actively share knowledge and support each other.
• Cutting-Edge Tools & Techniques — Get hands-on experience with ML, Bayesian methods, and LLMs to solve real business challenges.
• Data-Driven Culture — Thrive in an environment where data informs every decision and drives continuous improvement.

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Data Architect.

Must-Have Skills

• Data Architecture (8+ years, 3+ as architect)
• Enterprise data architecture — conceptual, logical, physical modeling
• Lakehouse architecture patterns — medallion architecture, data mesh principles
• Hybrid data architecture — on-prem ↔ cloud data movement, consistency, governance
• Data modeling — dimensional modeling, Data Vault 2.0, or similar for analytical workloads

• Cloudera / Hadoop Ecosystem (Critical)
• Cloudera Data Platform (CDP) — architecture, administration, security
• Apache Hive / Iceberg — table formats, partitioning strategies, compaction
• Apache Spark on Cloudera — performance tuning, resource management
• HDFS / Ozone — storage architecture, replication, tiering
• Apache Ranger / Knox — security, access control, audit
• Query & Analytics Layer
• Starburst / Trino — federated query architecture, connector management, caching strategies
• Tableau — data source architecture, extract vs. live connections, semantic layer design
• SQL optimization for analytical workloads — join strategies, materialized views, caching
• Streaming & Integration
• Apache Kafka — topic design, schema registry (Avro/Protobuf), exactly-once semantics
• CDC (Change Data Capture) patterns — Debezium, Kafka Connect
• ETL/ELT pipeline design — batch and streaming patterns
• Apache Airflow — DAG design for complex data pipelines
• Governance & Quality
• Informatica — data catalog, data quality, metadata management
• Data governance frameworks — data ownership, stewardship, lineage
• ABAC implementation for data access (attribute-based access control)
• Data quality metrics and monitoring
• Business glossary management

• Cloud Data Architecture (AWS)
• S3 — data lake storage patterns, lifecycle policies, storage classes
• AWS Glue — catalog, ETL jobs
• Lake Formation — fine-grained access control
• Hybrid integration — AWS Direct Connect, data replication strategies
   

Nice-to-Have

• Telco data models (CDR, network events, subscriber data, billing)
• Experience migrating from traditional Hadoop to modern lakehouse
• Data Mesh implementation experience
• Cost optimization for large-scale data platforms
• DAMA-DMBOK or equivalent data management certifications
   

Engagement Model

• Full-time staff augmentation (embedded in team)
• Business trips to Baku every 2 month
• Must overlap with Baku working hours (GMT+4)
• English fluency required

About Us

We are a newly funded MilTech startup building an on-premises platform for automated annotation of petabytes of UAV video and training computer vision models for autonomous flight. We have a strategic partnership with the largest Ukrainian UAV manufacturer and access to what is the largest privately owned UAV video dataset in the world. We are at the very beginning — the technical plan exists, the funding is secured, the data is real — and now we need the right people to turn it into reality.

The Role

We are looking for a Data Annotator / CVAT Specialist to join the founding team. You will be the person who turns raw UAV video into the high-quality labeled datasets that our ML models are trained on. This is not bulk labeling work — you will help define annotation standards, manage the CVAT platform, build quality control workflows, and directly shape the data that drives our autonomous flight models.

You will work closely with the ML engineering team to establish the annotation pipeline from scratch: from ontology design and labeling policy through annotation execution, quality assurance, and feedback loops that continuously improve both label quality and annotation speed.

What You Will Own

CVAT Administration & Workflow
- Set up projects, tasks, and jobs; manage annotation workflows and task routing
- Configure AI-assisted annotation: integrate pre-trained models for auto-labeling and tracking
- Manage user roles, permissions, and review pipelines within CVAT
- Handle data import/export across formats (COCO, YOLO, MOT, CVAT XML)

Annotation Execution
- Annotate UAV video clips using bounding boxes, multi-object tracking (Track Mode with keyframes and interpolation), and classification labels
- Handle complex scenarios: occluded objects, crowded scenes, night/low-visibility footage, fast-moving targets
- Achieve and maintain high throughput without sacrificing label quality

Ontology & Labeling Policy
- Collaborate with the ML team to define and refine the annotation ontology (class definitions, examples, edge cases)
- Document labeling rules: occlusion/truncation handling, minimum box sizes, track start/end criteria, disappearance rules
- Maintain and update annotation guidelines as new classes or scenarios emerge

Quality Control
- Execute the QC pipeline: gold set calibration, double-labeling for inter-annotator agreement, review workflows
- Run automated validation checks: geometry (out-of-frame, zero-area, broken aspect ratios), temporal continuity (teleporting boxes, scale jumps, broken tracks)
- Track quality metrics: agreement scores (IoU + class match), rework rates, model-vs-human correction rates
- Identify systematic errors and feed them back into guideline updates and annotator calibration

Scaling & Active Learning Support
- Process pre-labeled data from ML models: review, correct, and approve auto-annotations based on confidence routing (high/mid/low)
- Prioritize annotation effort on hard cases (low confidence, rare classes, difficult conditions)
- Provide structured feedback to the ML team on where pre-labels consistently fail, driving retraining priorities

What We Are Looking For

Must Have
- 2+ years of hands-on experience in data annotation for computer vision (object detection, tracking, or segmentation)
- Strong proficiency with CVAT — project setup, Track Mode, interpolation, AI-assisted annotation, import/export
- Experience annotating video data (not just static images) — understanding of temporal consistency and tracking
- Familiarity with annotation formats: COCO, YOLO, MOT, Pascal VOC
- Attention to detail and ability to maintain high label quality at volume
- Experience with quality control processes: review workflows, inter-annotator agreement, gold sets
- Comfortable working in Linux environments and with self-hosted tools

Strong Plus
- Experience administering a self-hosted CVAT deployment (Docker-based setup, Nuclio for serverless auto-annotation)
- UAV / drone / aerial imagery annotation experience
- Familiarity with other annotation tools (Label Studio, Supervisely, V7, Roboflow)
- Understanding of ML model evaluation metrics (mAP, IoU, precision/recall) and how annotation quality affects them
- Experience with active learning or pre-annotation workflows
- Basic Python scripting (format conversion, data validation, automation)
- MilTech or defense-related annotation work

What We Offer

- Join an early-stage team where your work directly determines the quality of the data behind our ML models
- Define annotation standards and QC processes from scratch — not just follow someone else's guidelines
- The largest privately owned UAV video dataset in the world — petabyte-scale, impossible to replicate
- Work closely with ML engineers and see how your annotations translate into model performance
- Opportunity to grow into annotation team lead as the team scales
- Open-source-first approach with no vendor lock-in
- Competitive salary
 

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better. We are now looking for a Middle Data Scientist to play a key role in reshaping the way we provide our solutions.
 

You could be a perfect match for the position if

You want to:

• Validate datasets to ensure data accuracy and consistency.
• Design proof-of-concept (POC) solutions to explore new approaches.
• Develop technical solutions by mapping requirements to existing tools and functionalities.
• Train models and create custom approaches for new domains.
• Troubleshoot data processing and model performance issues.

You have:

• 2+ years of experience in data science or a related field.
• Strong SQL skills for data manipulation and extraction.
• Proficiency in Python, with the ability to write modular and readable code for experiments and prototypes.
• A solid mathematical background, preferably in a Computer Science-related field.
• Expertise in scientific Python libraries, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.
• Familiarity with Time Series Forecasting methodologies.
• Experience in statistical testing, including A/B testing.
• 1+ years working with tabular and multimodal data (e.g., combining tabular data with text, audio, or images).
• Upper-intermediate or higher English level.

Soft skills:

• Analytical mindset and critical thinking to solve complex problems.
• Agile approach, with the ability to experiment and test hypotheses in a dynamic business environment.
• Business-oriented thinking, capable of translating complex models into clear business insights.
• Curiosity and a drive for continuous learning in the data domain.
• Strong team player, able to collaborate across cross-functional teams.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• Partial medical insurance coverage.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

Ми — українська MilTech-компанія, що створює майбутнє оборонних технологій. Ми розробляємо та виробляємо безпілотні системи й технологічні рішення, що вже довели свою ефективність у реальних бойових умовах. 

Наш відділ R&D об’єднує кращих інженерів, конструкторів, фахівців з RF і Hardware та багатьох інших. Завдяки власним виробничим потужностям ми забезпечуємо швидкий цикл впровадження інновацій — від ідеї до масового виробництва. Кожне оновлення продукту базується на прямому фідбеку від військових, що дозволяє нам створювати максимально актуальні рішення.
 

Твій виклик: Last Mile Targeting
 

Ми не граємо в симуляції заради статей на ArXiv. Твоє завдання — створити «мізки» дрона, здатні довести апарат до цілі в умовах повного РЕБ, шквального вітру та критичного браку обчислювальних ресурсів.
 

Це робота на межі можливостей: запуск RL-агентів на Raspberry Pi та подолання Sim2Real gap так, щоб модель не «втрачала» ціль через туман чи вібрації. Ми даємо тобі повний карт-бланш на архітектуру з нуля.
 

Що ти будеш робити:

• End-to-End Pipeline: Побудова архітектури навчання від симулятора до деплою на реальне залізо.
• RL Control: Розробка моделей керування (PPO, SAC, TD3), що приймають рішення на основі відеопотоку та сенсорів у real-time.
• Sensor Fusion: Реалізація стабільного керування (Kalman Filters або RL-native підходи) у зв'язці з Sensor Engineers.
• Sim2Real & Domain Randomization: Створення симуляційного середовища (Isaac Gym / AirSim / Custom UE) з глибокою рандомізацією для роботи в екстремальну погоду (сніг, дощ, низька видимість).
• Optimization: Квантування та прунінг моделей для досягнення стабільного FPS на обмежених ресурсах (Raspberry Pi, NVIDIA Jetson).
   

Наш ідеальний кандидат:

• Має досвід з RL-алгоритмами та розуміє, як змусити їх працювати в реальних системах.
• Знає, як наблизити фізику симулятора до реальності, щоб мінімізувати Gap при переносі на борт.
• Розуміє обмеження компактних комп’ютерів і вміє боротися за кожну мілісекунду інференсу.
• Готовий бути архітектором: самостійно обирати стек, симулятор та підхід.
   

Розглядаємо також: якщо ти маєш міцний бекграунд у CV/ML та досвід з дронами, але хочеш «увірватися» саме в Reinforcement Learning.
 

Буде плюсом: Досвід з TensorRT, PyTorch Mobile, SNPE, AIMET, Tensorflow Lite, gamedev (UE) або безпосередньо з БПЛА різних типів.
 

Чому варто приєднатися:

• Прямий вплив: Твій код буде «в полі» вже за лічені тижні, безпосередньо впливаючи на хід подій.
• Свобода та ресурси: Ти сам обираєш інструменти. Ми оплачуємо участь у топових конференціях (CVPR, NeurIPS, ICRA) та профільне навчання.
• R&D Полігон: Можливість миттєво тестувати гіпотези на реальних апаратах у найскладніших погодних умовах.
• Команда: Працюй пліч-о-пліч з експертами з GNC, RF, Hardware та топовими C++ розробниками.
• Стабільність: Офіційне працевлаштування, «біла» зарплата та бронювання.
• Турбота: Медичне страхування, 24 дні відпустки + додатковий вихідний на день народження.
• Self-care: Повна оплата лікарняних та 3 дні self-care на рік без жодних довідок.
• Розвиток: Корпоративна бібліотека, курси англійської, навчання Hard & Soft skills.

Готовий навчити дрони перемагати? Чекаємо на твоє CV!

ПРО ПОЗИЦІЮ

Вимоги:

• Досвід DS/MLE від 2 років
• Математичний бекграунд: вища математична освіта (КПІ ІПСА, МехМат Шевченко тощо), бажано олімпіадний досвід
• Глибокі знання алгоритмів і структур даних, глибоке розуміння ООП, глибокі теоретичні та практичні знання машинного та глибокого навчання
• Практичний досвід вирішення NLP та Tabular Data ML задач
• Високий рівень володіння Python, включаючи досвід роботи з бібліотеками машинного навчання і володіння принаймні одним із фреймворків глибокого навчання (Tensorflow, Keras, PyTorch)
• Вміння писати чистий, підтримуваний та ефективний код, готовий до production
• Вміння трансформувати бізнес-вимоги у технічні завдання для ML-рішень
• Досвід feature engineering
• Досвід роботи з Git та Docker
• Досвід роботи з базами даних (SQL/NoSQL) для отримання та підготовки даних для моделей

Буде плюсом:

• Досвід вирішення CV завдань
• Досвід успішних виступів на хакатонах/Kaggle
• Досвід роботи з Airflow на рівні запуску та моніторингу завдань
• Розуміння принципів паралелізму в Python та досвід роботи з відповідними бібліотеками

Приклади задач:

• Підвищення точності поточних CV, NLP та інших моделей
• Розробка нових моделей з нуля: від R&D та feature engineering до валідації
• Аналіз великих обсягів даних для пошуку інсайтів та формулювання гіпотез для моделювання

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).