Jobs Data Science

Remote – Full-time – Flexible Hours - Shifted schedule to EST (New York) timezone

About TenViz

TenViz Predictive Analytics builds AI-powered solutions that help Fortune 100 investors anticipate market shifts before they become consensus. We combine financial expertise, mathematical rigor, and AI research to deliver predictive analytics for institutional investors.

Your Expertise

• Strong interest in quantitative and algorithmic approaches
• BSc/MSc in Math, Physics or related field with solid background in statistics, linear algebra and probability theory
• Advanced Linear Algebra, Advanced Statistics, Using Linear Algebra methods in Statistical analysis
• 2+ years in data research, quantitative modeling, ML prototyping, and backtesting
• Skilled in Python, SQL, Git
• Experience with  experiment tracking, pipeline orchestration and workflow automation

Nice to have:

• Bayesian inference, reinforcement learning, or ensemble methods
• Financial econometrics, time-series forecasting, or regime modeling

What You’ll Do

• Design predictive models using probabilistic, ML, and hybrid approaches
• Analyze large-scale financial datasets to detect hidden patterns and early regime shifts
• Prototype and evaluate algorithms, from deep learning to Bayesian models
• Write production-grade research code in Python/SQL that integrates into pipelines
• Translate results into insights and themes investors can act on — not just outputs

Example projects:

• Forecasting inflation via commodity price signals
• Constructing probabilistic forecasts of currency moves around macroeconomic announcements
• Designing a Bayesian model to estimate recession probabilities from yield curve dynamics
• Designing a regime-aware ML pipeline that switches models depending on market conditions
• Creating hybrid ensembles that outperform traditional benchmarks

What’s in It for You

• Remote-first, flexible hours
• Paid vacation & holidays (after 8 months)
• Continuous learning: advanced ML/DL workshops, probabilistic methods, optimization
• Supportive, collaborative team — no micromanagement, focus on trust and creativity
• Work on real financial problems where your models influence billion-dollar decisions

Computer Vision engineer

DeepX is looking for a Computer Vision engineer

Core requirements:
- Python development experience
- Knowledge of popular data processing libraries (numpy, pandas, scipy etc)
- GIT, Linux, bash

Nice to have (or able to learn quickly):
- Hands-on experience with popular Machine Learning frameworks (OpenCV, Pytorch, Tensorflow, Keras, Yolo)
- Understanding of Computer Vision problem space
- Machine Learning and Artificial Neural Networks fundamentals
- Linux, Docker, gcc/make etc experience
- C++ and C, creating Python C extensions

A bit about DeepX company:
DeepX is an R&D intensive and innovation-driven consortium that provides Artificial Intelligence-powered Computer Vision solutions for businesses.
Please, take a look to find out more about us https://deepxhub.com/
We are a group of enthusiastic adherents who are passionate about the idea of improving this world’s safety by making Computer Vision technologies more advanced. Lifetime learning is our motto, we are admire ambition hard workers who are ready to face new challenges. If you feel like we might be on the same page, please, apply!

Responsibilities:

• Discover, envision and land Data Science, AI and Machine Learning opportunities alongside EPAM teams & clients
• Lead cross-functional EPAM and/or EPAM clients` teams through the journey of understanding business challenges and defining solutions leveraging AI, Data Science, Machine Learning and MLOps 
• Work with clients to deliver AI Products which provide value to end-users 
• Participate and drive EPAM competencies development, work on new EPAM offerings in AI, Data Science, ML and MLE space, as well as work on refining existing offerings 
• Bring your creative engineering mind to deliver real-life practical applications of Machine Learning 
• Work closely with DevOps practice on infrastructure and release planning 
   

Requirements:

• Consulting: Experience in exploring the business problem and converging it to applied AI technical solutions; expertise in pre-sales, solution definition activities  
• Data Science: 3+ years of hands-on experience with core Data Science, as well as knowledge of one of the advanced Data Science and AI domains (Computer Vision, NLP, Advanced Analytics etc.)  
• Engineering: Experience delivering applied AI from concept to production, familiarity, and experience with MLOps, Data, design of Data Analytics platforms, data engineering, and technical leadership
• Leadership: Track record of delivering complex AI-empowered and/or AI-empowering programs to the clients in a leadership position. Experience managing and growing the team to scale up Data Science, AI &ML capability is a big plus
• Excellent communication skills (active listening, writing and presentation), drive for problem solving and creative solutions, high EQ

About Keymakr

• Keymakr specializes in end-to-end dataset preparation, including video and image annotation and labeling for AI projects.
  We take a personalized approach, delivering customized solutions tailored to each client’s needs.

   

• Our strong in-house R&D team develops and adapts annotation tools for every client, allowing us to successfully handle even the most complex requirements.

About the Role:

• We are looking for a Data Management Specialist to manage, process, and maintain large volumes of data and media assets used in AI and technology projects.

   

• This role focuses on ensuring data integrity, consistency, and availability while optimizing workflows through automation and close collaboration with cross-functional teams.

   

Key Responsibilities:

1. Manage and manipulate data using Linux file systems and native OS tools;
2. Work with media files, including video formats, codecs, resolution, and frame rate (FPS);
3. Verify data integrity using checksum and verification tools;
4. Pack and unpack large data archives efficiently;
5. Automate data-related workflows using scripting languages;
6. Prepare, structure, and maintain datasets in structured formats;
7. Maintain cloud-based data storage and perform data migration;
8. Collaborate with Project, QA, and Technical teams to ensure smooth data operations;
9. Clearly and consistently document workflows, processes, and task updates.

Technical Skills:

1. Strong knowledge of Linux file systems and administration (Ubuntu/Debian, 2+ years);
2. Experience with Windows OS administration;
3. Proficiency in Python and Bash / Shell scripting;
4. Experience with archive management tools for large datasets;
5. Knowledge of checksum verification tools (md5sum, sha256sum);
6. Tools for checking video properties, codecs, and formats;
7. Solid knowledge of JSON and CSV formats;
8. Experience with cloud storage platforms: AWS S3, Google Cloud Storage, or Azure;
9. Familiarity with JIRA, Slack, Confluence, and Google Docs.

Nice to Have:

1. Experience with point clouds / 3D data;
2. Strong understanding of complex technical specifications;
3. Experience working with large-scale datasets;
4. English & Communication;
5. English level B2 (Upper-Intermediate) or higher;
6. Ability to read and understand technical documentation and project requirements;
7. Clear written communication in English (reports, updates, documentation);

8. Participation in English-language meetings when required.

    

If you want, I can also:

• tailor it for remote / hybrid / office format,
• shorten it to fit DOU’s compact job posting style,
• or adjust it to a more technical / more business-oriented tone.

We’re looking for a proactive Data Scientist to join our growing team and help us redefine the future of eSports betting! You will develop and implement advanced models for esports betting, focusing on games such as Dota 2, League of Legends, etc. Oversee the entire model development lifecycle, including design, testing, and performance optimization.

What you’ll be doing:

• Develop and implement betting models using Python and Golang.
• Design and optimize mathematical models, including statistical models, classical machine learning techniques, and neural networks.
• Analyze the performance and impact of models, ensuring operational efficiency.
• Prototype and assess models to evaluate their effectiveness and user acceptance.
• Integrate models with existing systems and optimize performance.
• Collaborate with backend and frontend teams for seamless implementation and decision-making.
• Conduct in-depth statistical analysis and apply machine learning methods to enhance forecasting accuracy.

What we’re looking for:

• 3+ years of commercial experience with Python.
• Strong knowledge of statistics and practical experience with ML techniques.
• Proven expertise in mathematical modeling, including statistical methods, classical ML approaches, and neural networks.
• Strong data processing skills (validation, parsing, visualization).
• Understanding business logic of decisions and analytical thinking ability.
• Excellent communication skills and the ability to work in a team.
• Ability to assess the business value of tasks.
• English – Intermediate level.
• Nice to have: Higher education in computer science, mathematics, statistics, or a related discipline is a plus.

• Nice to have: Experience in the betting industry or related fields is an advantage.

   

What We Offer:

• Your wellbeing and a comfortable work environment are our top priorities:
• Flexible schedule & work format (office/hybrid): work where and when you feel most productive.
• 20 paid + 15 unpaid vacation days: take time off whenever you need to reset.
• An extra day off on your birthday — celebrate it your way!
• Medical insurance: take care of your health with extended coverage (available in Ukraine only).
• 22 sick days: 8 days without a doctor’s note (for sick leave or mental health), 10 with a note, plus 4 Personal Days per year — for personal matters, when it is necessary.
• Gifts and bonuses for life’s big moments: weddings, new babies, kindergarten support (available in Ukraine only).

Who We Are:

We’re DATA.BET — a product-driven IT company transforming the world of sports, esports, and virtual betting with our innovative sportsbook solution. 

Since 2017, we’ve been building tech that directly shapes the industry.
Our team of experts blends hands-on experience with AI technologies to deliver cutting-edge solutions that set new standards in betting.

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.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We are looking for a Computer Vision / Machine Learning Engineer to develop offline CV models for industrial visual inspection.

Your main task will be to design, train, and evaluate models on inspection data in order to:

• Improve discrimination between good vs. defect samples
• Provide insights into key defect categories (e.g., terminal electrode irregularities, surface chipping)
• Significantly reduce false-positive rates, optimizing for either precision, or recall
• Prepare the solution for future deployment, scaling, and maintenance
•  

Key Responsibilities:
Data Analysis & Preparation
- Conduct dataset audits, including class balance checks and sample quality reviews
- Identify low-frequency defect classes and outliers
- Design and implement augmentation strategies for rare defects and edge cases
Model Development & Evaluation
- Train deep-learning models on inspection images for defect detection
- Use modern computer vision / deep learning frameworks (e.g., PyTorch, TensorFlow)
- Evaluate models using confusion matrices, ROC curves, precision–recall curves, F1 scores and other relevant metrics
- Analyze false positives/false negatives and propose thresholds or model improvements
Reporting & Communication
- Prepare clear offline performance reports and model evaluation summaries
- Explain classifier decisions, limitations, and reliability in simple, non-technical language when needed
- Provide recommendations for scalable deployment in later phases (e.g., edge / on-prem inference, integration patterns)

Candidate Requirements:
Must-have:
- 1-2 years of hands-on experience with computer vision and deep learning (classification, detection, or segmentation)
- Strong proficiency in Python and at least one major DL framework (PyTorch or TensorFlow/Keras)
- Solid understanding of:

• Image preprocessing and augmentation techniques
• Classification metrics: accuracy, precision, recall, F1, confusion matrix, ROC, PR curves
• Handling imbalanced datasets and low-frequency classes

- Experience training and evaluating offline models on real production or near-production datasets
- Ability to structure and document experiments, compare baselines, and justify design decisions
- Strong analytical and problem-solving skills; attention to detail in data quality and labelling
- Good communication skills in English (written and spoken) to interact with internal and client stakeholders

Nice-to-have:
- Experience with industrial / manufacturing computer vision (AOI, quality inspection, defect detection, etc.)
- Familiarity with ML Ops/deployment concepts (ONNX, TensorRT, Docker, REST APIs, edge devices)
- Experience working with time-critical or high-throughput inspection systems
- Background in electronics, semiconductors, or similar domains is an advantage
- Experience preparing client-facing reports and presenting technical results to non-ML audiences

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- 40 days of PTO;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

Who we are  

MINT is the leader in Advertising Resource Management (ARM) software, driving marketing transformation in the age of agentic AI. At the core of our innovation is an open enterprise platform that deploys autonomous AI agents to augment human teams across the marketing and advertising value chain, connecting marketing performance with enterprise growth and real business impact. 

Thanks to a diverse team of over 300 professionals worldwide, we integrate technology, data, and agentic intelligence to redefine how global brands and agencies plan, execute, and optimize their advertising investments. 

With the recent acquisitions of technology leaders Redmill Solutions and info³, MINT has further expanded its unified ecosystem, completing the long-awaited connection of media planning, buying, and execution within one intelligent environment. 

The Role 

We’re looking for a Data Science Associate to support the development of a cutting-edge agentic AI suite for full cycle media operations, from media planning, activation to financial reconciliation. Your job will focus on designing, developing and deploying end-to-end data initiatives - from data ingestion to data presentation, from proof of concept to production. In this role, you'll have the opportunity to shape product direction and technical development.  

This is a consultancy engagement, not an employment contract. The selected consultant will work independently, bringing their specialized knowledge and experience to our projects. 

What you'll be doing  

• Contribute to the design, development, and deployment of data science solutions, from exploration to production 
• Work closely with product, engineering and solution consultants’ teams to translate business challenges into scalable data products 
• Develop, evaluate, and deploy machine learning models and data pipelines for real-world applications 
• Explore and integrate new technologies such as LLMs, MCP/A2 and AI agents to enhance our products 
• Explore building a standalone agentic workforce for media operations  
• Ensure data quality and integrity across multiple sources and processing stages 
• Communicate findings and insights clearly to technical and non-technical stakeholders 
• Assist in identifying and implementing SOTA and emerging AI/ML techniques  
• Contribute to team-wide technical decisions, planning, and long-term strategy 

This role will be a great fit if you have:  

• 1+ years of experience in data science with a solid foundation in statistics and machine learning 
• Proficiency in Python (and its core data/ML libraries) and SQL 
• Hands-on experience with ETL processes, large datasets (1M+ rows), and data cleaning and validation 
• Knowledge of frameworks like LangChain, Langraph 
• Ability to design and customize AI agents using RAG and similar techniques 
• Familiarity with AWS or another major cloud platform 
• Experience with time-series forecasting, recommender systems, NLP, or optimization problems  
• Strong communication and presentation skills, with the ability to bridge technical and non-technical perspectives 
• Self-driven and comfortable handling tasks independently in a remote setup 

We would also appreciate: 

• Familiarity with Docker or Kubernetes, CI/CD pipelines, monitoring tools, and Git 
• Previous experience with setting up MCP/A2 integrations is desired but not required 
• Background or interest in the advertising or marketing technology space 

Interview Process 

Candidates can expect the following steps in our interview process: 

• HR Video Interview (30 minutes): A virtual interview with HR to provide an overview of the company and the role, as well as to gain insight into your experience and background. 
• Technical Interview with Tech team (1 hour): A virtual interview with the Data Science Team Lead and/or other Team members, focused on your technical expertise, past experience, and problem-solving approach. 
• Offer: after completing the interview process, successful candidates will receive an offer. 

MINT is committed to a diverse and inclusive workplace. MINT AI is an equal opportunity employer and does not discriminate on the basis of age, race, religion, color, national origin, gender, gender identity, gender expression, sexual orientation, immigration status, medical condition, protected veteran status, disability, genetic information, political views or activity, or other legally protected status.  

We are looking for a talented and motivated Machine Learning Engineer to join our team and work on cutting-edge projects in the fields of IoT, robotics, and AI. You will also collaborate with other engineers and researchers to implement machine learning algorithms and optimize performance.

Required Skills:

•2 years experience in the industry

•Experience in building AI/ML based products

•Experience in C++ Software Development using modern standards (C++ 11,14,17)

•Professional knowledge of Python programming and hands-on experience working with libraries such as OpenCV, Pandas, NumPy

•Familiarity with Python ML frameworks such as Pytorch and/or Tensorflow/Keras

•Understanding of designing and implementing various stages ML pipeline

•Understanding base ML algorithms and data processing techniques

•Good analytical skills, and mathematical abilities, being able to translate complex data into actionable insights

Will Be a Plus:

•Experience Embedded C/C++

•Qt experience

We offer:

• Competitive compensation

• Performance evaluations

• Full accounting assistance and support

• Regular annual vacation is 20 working days off

• 100% paid sick leave upon provision of the relevant document(s)

• Holidays are provided according to the residence country’s Law

• Improvement of English language knowledge with our teacher

• Smart and useful presents for our employees and their kids

• Great atmosphere, creative corporate parties, and true

Why P-Product:

• Though we have many different projects with different histories and of different ages, we always grant interesting work, challenging tasks, interesting collaboration, and positive thinking

• We grant individual approach to each of our employees elaborating on him or her career growth strategies

• We invest into the technical education of our employees finding them special courses, trainings, conferences, and meetups

• We organize and conduct a great number of local team-building events and activities

• Though often working in the customer’s team, our employee know that they are carried about, protected, and helped by the P-Product back-office team

• Our specialists are never alone with their difficult tasks, they always have someone to get a helping hand from

• We understand that communication matters and help our employees with this

• People make P-Product value

• We do not declare, we do :)

We are now looking for a Data Scientist with LLM usage background to join our development team and help build innovative solutions in medical tourism.
 

Your Role:

As a Data Scientist, you will:

• Extract medical entities and patterns from large volumes of text documents including medical reports, patient histories, and clinical notes using NLP techniques (NER, entity linking) to identify diagnoses, procedures, medications, and symptoms for automated document processing and intelligent search capabilities.
• Implement clustering and similarity detection algorithms to group similar medical cases, treatment patterns, and patient profiles, enabling better matching between patients and healthcare providers through unsupervised learning methods (K-means, DBSCAN, hierarchical clustering) and semantic similarity measures.
• Engineer data architecture for new chatbot features and integrate them with existing tools like CRM, databases, and analytics services.
• Optimize AI solutions to enhance system speed, stability, and quality, including refactoring and improving existing functionalities, while incorporating state-of-the-art AI methodologies and frameworks.
• Build personalized offer-generation services by aggregating data from forms, chats, attached files, clinic price lists, and historical databases to generate real-time, patient-specific proposals.
• Work with databases (MySQL, PostgreSQL, MongoDB) to design scalable structures, write efficient queries, and ensure data security and integrity.
• Test, refactor, and maintain code while documenting key decisions and ensuring clean, maintainable systems.
• Support our chatbot assistant by designing and implementing advanced AI-driven modules (multi-layered task decomposition for optimal results), leveraging Natural Language Processing + LLM services to enhance conversational capabilities and user experience.
• Enhance business processes by brainstorming with Sales and Product teams, suggesting improvements, and exploring new AI/ML advancements (e.g., OpenAI, Lama, other ML tools) to integrate novel solutions into existing workflows.
   

What You Need:

• 4+ years of experience in data science or related fields.
• Strong expertise in Python (preferably with FastAPI).
• A solid understanding of modern big data analysis approaches, clustering, and correlation searches.
• Prompt engineering (OpenAI / Claude models)
• Database architecture skills
• Proficiency in MySQL and MongoDB
• Hands-on experience with AI tools for tasks like text/image analysis and content generation.

What We Offer

• Competitive salary aligned with market standards.
• Engaging projects in the medical tourism and travel industries.
• A collaborative environment of Python and PHP engineers, frontend developers, product managers, and medical coordinators.
• Comprehensive benefits package, including:
  • 22 paid vacation days annually.
  • Medical insurance.
  • Compensation for sports activities.
  • Remote work flexibility with an 8-hour workday starting between 8–10 AM.
• Opportunities to grow your skills with regular updates to your compensation.
• The chance to impact a meaningful product that transforms lives.

Azzurro.io is looking for ML Engineer.

Location: Remote (Company based in Seattle)

About the Client: Our client partners with brands to improve their sales and visibility on Amazon through optimized advertising campaigns and keyword strategies. Using data-driven insights, they help clients increase their impact in the marketplace.

Role Overview: As a Data Scientist, you'll build predictive models using time series data (e.g., product ranks, keyword performance, ad campaigns) to help optimize our client’s Amazon strategies. You’ll analyze, clean, and transform data to train ML models that improve ad performance and drive sales.

Responsibilities:

• Predictive Modeling: Develop and refine models to analyze product rankings and campaign performance.
• Data Preparation: Extract, clean, and transform large datasets for analysis and modeling.
• Regression Analysis: Build regression models to forecast trends and improve keyword strategies.
• Model Optimization: Use techniques like feature engineering and hyperparameter tuning to improve model performance.

Tech Stack:

• Core Technologies: AWS, MySQL, Python.
• Data & ML Tools: Python libraries (NumPy, pandas), frameworks (e.g., TensorFlow or similar).

Qualifications:

• Strong background in analytics, mathematics, and experience with time series data.
• Proficiency in Python, including data libraries (NumPy, pandas) and ML frameworks (e.g., TensorFlow, PyTorch).
• Experience building regression models and optimizing predictive algorithms.
• Working knowledge of SQL for querying large datasets.
  
  P.S. please pay your attention that this position is open in Azzurro.io company, not Pics.io.

Our Customer:

Our customer is a global, data-driven digital advertising technology company operating at large scale across mobile apps and web platforms.
 

Your Tasks:

• Analyze large, complex datasets to uncover patterns, insights, and business opportunities;
• Design, build, and own scalable, end-to-end data pipelines;
• Develop and productionize advanced machine learning models and algorithms, particularly in monetization-related domains;
• Build and maintain data models for real-time (online) processing;
• Contribute to the creation of new data-driven products and continuously improve existing ones;
• Collaborate with Product, BI, Analytics, DevOps, R&D, and Marketing teams to deliver complete solutions;
• Lead full production releases, including requirements analysis, testing, monitoring, result evaluation, and rapid response to critical issues.
   

Required Experience and Skills:

• 6+ years of experience as a Data Scientist with a strong foundation in machine learning concepts and models;
• Previous experience in the Ad-Tech industry;
• Hands-on experience working on large-scale, high-load systems processing billions of requests per second;
• Hands-on experience with Python including writing production-ready code and working with modern Python frameworks and tooling;
• Experience with data science / ML libraries and models, such as regression and classification models (e.g. XGBoost, LightGBM), recommendation systems, and related ML techniques;
• Solid understanding of databases and SQL for data analysis and retrieval;
• Experience with monitoring and alerting tools such as Grafana and Kibana;
• Proven experience working in real-time / online environments;
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field;
• Strong end-to-end ownership mindset: ability to take solutions from research and experimentation through implementation and production;
• Fluent English with strong communication and collaboration skills.
   

Would Be a Plus:

• Familiarity with the programmatic advertising ecosystem (DSPs, SSPs, ad exchanges);
• Experience with relational databases (e.g. Vertica, VoltDB) and non-relational databases (e.g. MongoDB);
• Experience working with PMML.
   

Working conditions

5-day working week, 8-hour working day;

Remote work.

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).

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We are looking for a Computer Vision / Machine Learning Engineer to develop offline CV models for industrial visual inspection.

Your main task will be to design, train, and evaluate models on inspection data in order to:

• Improve discrimination between good vs. defect samples
• Provide insights into key defect categories (e.g., terminal electrode irregularities, surface chipping)
• Significantly reduce false-positive rates, optimizing for either precision, or recall
• Prepare the solution for future deployment, scaling, and maintenance
•  

Key Responsibilities:
Data Analysis & Preparation
- Conduct dataset audits, including class balance checks and sample quality reviews
- Identify low-frequency defect classes and outliers
- Design and implement augmentation strategies for rare defects and edge cases
Model Development & Evaluation
- Train deep-learning models on inspection images for defect detection
- Use modern computer vision / deep learning frameworks (e.g., PyTorch, TensorFlow)
- Evaluate models using confusion matrices, ROC curves, precision–recall curves, F1 scores and other relevant metrics
- Analyze false positives/false negatives and propose thresholds or model improvements
Reporting & Communication
- Prepare clear offline performance reports and model evaluation summaries
- Explain classifier decisions, limitations, and reliability in simple, non-technical language when needed
- Provide recommendations for scalable deployment in later phases (e.g., edge / on-prem inference, integration patterns)

Candidate Requirements:
Must-have:
- 1-2 years of hands-on experience with computer vision and deep learning (classification, detection, or segmentation)
- Strong proficiency in Python and at least one major DL framework (PyTorch or TensorFlow/Keras)
- Solid understanding of:

• Image preprocessing and augmentation techniques
• Classification metrics: accuracy, precision, recall, F1, confusion matrix, ROC, PR curves
• Handling imbalanced datasets and low-frequency classes

- Experience training and evaluating offline models on real production or near-production datasets
- Ability to structure and document experiments, compare baselines, and justify design decisions
- Strong analytical and problem-solving skills; attention to detail in data quality and labelling
- Good communication skills in English (written and spoken) to interact with internal and client stakeholders

Nice-to-have:
- Experience with industrial / manufacturing computer vision (AOI, quality inspection, defect detection, etc.)
- Familiarity with ML Ops/deployment concepts (ONNX, TensorRT, Docker, REST APIs, edge devices)
- Experience working with time-critical or high-throughput inspection systems
- Background in electronics, semiconductors, or similar domains is an advantage
- Experience preparing client-facing reports and presenting technical results to non-ML audiences

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- 40 days of PTO;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.

Our Customer:

Our customer is a global, data-driven digital advertising technology company operating at large scale across mobile apps and web platforms.

Your Tasks:

• Analyze large, complex datasets to uncover patterns, insights, and business opportunities;
• Design, build, and own scalable, end-to-end data pipelines;
• Develop and productionize advanced machine learning models and algorithms, particularly in monetization-related domains;
• Build and maintain data models for real-time (online) processing;
• Contribute to the creation of new data-driven products and continuously improve existing ones;
• Collaborate with Product, BI, Analytics, DevOps, R&D, and Marketing teams to deliver complete solutions;
• Lead full production releases, including requirements analysis, testing, monitoring, result evaluation, and rapid response to critical issues.

Required Experience and Skills:

• 6+ years of experience as a Data Scientist with a strong foundation in machine learning concepts and models;
• Previous experience in the Ad-Tech industry;
• Hands-on experience working on large-scale, high-load systems processing billions of requests per second;
• Hands-on experience with Python including writing production-ready code and working with modern Python frameworks and tooling;
• Experience with data science / ML libraries and models, such as regression and classification models (e.g. XGBoost, LightGBM), recommendation systems, and related ML techniques;
• Solid understanding of databases and SQL for data analysis and retrieval;
• Experience with monitoring and alerting tools such as Grafana and Kibana;
• Proven experience working in real-time / online environments;
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field;
• Strong end-to-end ownership mindset: ability to take solutions from research and experimentation through implementation and production;
• Fluent English with strong communication and collaboration skills.

Would Be a Plus:

• Familiarity with the programmatic advertising ecosystem (DSPs, SSPs, ad exchanges);
• Experience with relational databases (e.g. Vertica, VoltDB) and non-relational databases (e.g. MongoDB);
• Experience working with PMML.

Working conditions

• 5-day working week, 8-hour working day;
• Remote work.