Jobs Data Scientist

We are growing our AI/ML team and are looking for a Senior Machine Learning Engineer to take a leading role in building and scaling applied machine learning systems that power personalization and discovery features across our platform. A key initiative is a large-scale recommendation system based on a two-tower architecture, deployed on AWS and serving millions of users. This position is not limited to a single use case. You will also contribute to other machine learning and data science initiatives, helping define best practices and raising the overall ML maturity of the team.

What you’ll drive:

Technical Leadership & Ownership

• Take technical ownership of core components of recommendation and personalization systems (retrieval, ranking, evaluation).
• Design and evolve two-tower / embedding-based retrieval models and downstream rankers.
• Drive architectural and modeling decisions with a strong understanding of trade-offs between model quality, system complexity, latency, and cost.
• Define and promote best practices for ML system design, experimentation, evaluation, and deployment.
• Review ML designs, pipelines, and code with a focus on correctness, maintainability, and production readiness.
• Act as a technical point of reference for ML-related decisions within the team

Hands-on ML Development

• Develop, train, and improve ML models for retrieval and ranking use cases.
• Work with embedding-based deep learning models and classical ML approaches.
• Perform in-depth data analysis, feature exploration, and systematic error analysis.
• Build reproducible experiments and robust offline evaluation pipelines.
• Optimize models for both offline metrics and online business KPIs.
• Design and operate batch and real-time training and inference workflows in a cloud environment, with awareness of scalability and cost trade-offs.

Experimentation & Production

• Design, run, and analyze offline experiments and online A/B tests.
• Own ML components in production, with a strong focus on reliability, observability, and safe iteration.
• Monitor model performance and data quality in production.
• Collaborate on scalable training and serving infrastructure for ML systems.
• Participate in incident analysis related to ML systems and contribute to root-cause analysis and long-term fixes.
• Design ML systems with failure modes in mind, including fallbacks and graceful degradation.

Collaboration & Mentorship

• Work closely with Data Engineering on data pipelines and feature generation.
• Partner with Product and Analytics to translate business goals into clear ML objectives and success metrics.
• Act as a technical mentor for ML engineers, providing guidance on modeling, experimentation, and production ML.

• Provide constructive feedback through code reviews and design discussions, supporting the growth of the team.

   

What makes you a GR8 fit:

Must-have

• 5+ years of experience in Machine Learning / Applied Data Science.
• Strong Python skills and experience writing production-quality ML code.
• Solid foundation in core ML and data science tools: NumPy, Pandas, scikit-learn, etc.
• Hands-on experience with deep learning frameworks (PyTorch or TensorFlow).
• Practical experience with embedding models and similarity-based retrieval.
• Experience with tree-based models (LightGBM, XGBoost).
• Strong understanding of ML evaluation, experimentation, and applied statistics.
• Experience deploying, operating, and maintaining ML models in production environments.
• Proficiency with Git, Linux, Docker, and standard ML development workflows.

• Practical experience deploying ML systems in a cloud environment (AWS or equivalent).

   

Nice-to-have

• Direct experience with recommendation systems or search-related problems.
• Experience designing or operating two-tower / dual-encoder architectures.
• Familiarity with ANN methods and large-scale retrieval (e.g., FAISS or equivalents).
• Understanding of common ML production challenges (training–serving skew, data leakage, model drift).
• Experience collaborating on data pipelines and feature engineering at scale.
• Experience leading or mentoring other ML engineers.
• Experience with experiment automation and hyperparameter optimization (Optuna, Ray /Tune, Hyperopt, or cloud-native equivalents).
• Background in high-scale consumer products (content, gaming, media, marketplaces).

• Experience working with CI/CD pipelines for ML workflows (training, evaluation, deployment).

   

Tech Stack

• Languages: Python, SQL.
• Core ML / DS: NumPy, Pandas, scikit-learn.
• Deep Learning: PyTorch / TensorFlow.
• ML Models: LightGBM, XGBoost.
• Retrieval: Embeddings, ANN.
• Cloud & Data: AWS, SageMaker, S3, Glue.
• Dev & MLOps: Git, Docker, Linux.

We are looking for a Middle Machine Learning Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Key Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members.

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

Welcome to King Group - a place where the best people from the IT and gambling industries meet to do amazing things together. We operate numerous projects in the iGaming sector in the markets of Ukraine, Europe and the USA, invest in venture startups, promising ideas and people.
 

One of our companies is a game studio that deals with the full cycle of iGaming product development. From idea to release, we combine creativity, modern technologies and deep analytics to create a unique gaming experience. Our mission is to excite, inspire and shape the future of the industry.

Our company is looking for a math expert who has a drive and passion (perhaps some experience) for games.

Key skills (it's not necessary to have all key skills, but more is better than less):

• Higher education in mathematics or related fields (related to research, analytics or data processing);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Advanced knowledge of MS Excel (statistical, mathematical functions);
• Be proficient at one (at least) programming language (Python is preferable);
• Knowledge of one of the CAS (Mathematica, Mathcad, Maxima);
• Have a strong math background (especially probability theory, statistics, combinatorics);
• Have previous experience in gaming industry or (and) have experience in playing slots (or any other probabilistic games (poker, blackjack, etc));
• Understand the time and memory complexity of your code;
• Be keen on details (Yes, it's really important at this position);
• Understanding OOP Concepts;
• Experience in developing mathematical models.
   

Nice to have:

• Experience in using git;
• Experience in using JIRA.
   

Responsibilities: 

• Prepare math for slot games;
• Discuss with business/ propose new game ideas/new feature ides;
• Implement game logic of new features, games;
• Gather games' statistics by precise calculations / running simulations of the games;
• Make games attractive for players from the math side.
   

Why we:

• Social Package;
• Medical care;
• Sick Days;
• Professional development support;
• Family-like atmosphere. You can check it out yourself ;)
• Great career prospects.
  
  Do you want to grow with us? Do you have the desire to take an active part in creating a product? Send your resume and let's get to know each other ;)

We are seeking an experienced Data Scientist with a passion for large language models (LLMs) and cutting-edge AI research. In this role, you will design and prototype data preparation pipelines, collaborating closely with data engineers to transform your prototypes into scalable production pipelines, design and implement a state-of-the-art evaluation and benchmarking framework to measure and guide model quality, and do end-to-end LLMs training. You will work alongside top AI researchers and engineers, ensuring our models are not only powerful but also aligned with user needs, cultural context, and ethical standards.

What you will do

• Curation of datasets for pre-training, supervised fine-tuning, and alignment;
• Research and develop best practices and novel techniques in LLM training and evaluation pipelines;
• Collaborate closely with data engineers, annotators, linguists, and domain experts to scale data processes, define evaluation tasks and collect high-quality feedback.

Qualifications and experience needed
Education & Experience:

• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP;
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.

GenAI & NLP Expertise:

• Practical experience with fine-tuning LLMs / VLMs models;
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.

ML & Programming Skills:

• Strong experience with deep learning frameworks such as PyTorch or JAX for building models;
• Ability to write efficient, clean code and debug complex model issues.

A plus would be
Advanced NLP/ML Techniques:

• Applied experience using Reinforcement Learning in NLP / LLM settings;
• Prior work on LLM safety, fairness, and bias mitigation;
• Experience generating and curating synthetic datasets for Supervised Fine-Tuning (SFT), including quality control and scaling considerations.

Research & Community:

• Publications in NLP/ML conferences or contributions to open-source NLP projects;
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.

MLOps & Infrastructure:

• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow);
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models;
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.

Problem-Solving:

• Innovative mindset with the ability to approach open-ended AI problems creatively;
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace;
• Remote onboarding;
• Performance bonuses;
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners;
• Health and life insurance;
• Wellbeing program and corporate psychologist;
• Reimbursement of expenses for Kyivstar mobile communication.

Role Summary:
We are looking for a Senior Vibe Developer—a senior AI-driven product engineer who turns business ideas into actionable, AI-powered solutions. You will join the team to evaluate current processes, design AI-enabled workflows, implement features, and optimize our development lifecycle using AI tools, models, and agents. You are passionate about AI, follow the latest trends, and know how to apply AI strategically to solve real business problems efficiently.

Responsibilities:

Evaluate & Modernize Workflows:

Analyze current processes across product design, development, and operations.

Identify opportunities to streamline, automate, and optimize using AI tools.

Define rules, standards, and AI-driven processes to improve productivity and quality.

Translate Business Ideas into AI Solutions:

Collaborate with product and business teams to understand goals and constraints.

Design AI-enabled workflows, prototypes, and solutions to make ideas feasible.

Implement features end-to-end, including rules for design, notifications, or automation.

Hands-On AI Implementation:

Select and fine-tune open-source or commercial LLMs for specific tasks.

Build small AI-powered tools, agents, or components to integrate into workflows.

Balance AI model performance, cost (tokens), latency, and output quality.

AI System Design & Process Ownership:

Define and enforce best practices for AI usage across the company.

Establish rules for memory, context, versioning, and evaluation of AI outputs.

Ensure reliability, observability, and maintainability of AI-powered features.

Innovation & Continuous Learning:

Stay up-to-date with AI releases, techniques, and best practices.

Evaluate new AI models, agents, and tools for applicability and efficiency.

Share knowledge and patterns with the team to increase adoption and velocity.

Requirements:

Experience: 5+ years as a software engineer or AI engineer; proven hands-on experience shipping production-quality software.

Technical Skills:

Python required; familiarity with TypeScript/Node.js, Go, or Java a plus.

Experience with LLMs (open-source or commercial), including training, fine-tuning, evaluation, and deployment.

Knowledge of AI workflows, memory management, prompt engineering, and token management.

Mindset:

Passionate about AI and innovation, keeps up with trends and new releases.

Strong product and business understanding; able to translate ideas into technical solutions.

Hands-on problem solver with architectural thinking.

Strong ownership, ability to drive processes and execute independently.

Nice-to-Have:

Experience building AI-enabled agent workflows or internal tooling.

Exposure to LLMOps best practices (tracing, guardrails, evals, prompt/version management).

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

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.