Вакансии Data Scientist / Machine learning Engineer

Our partner is revolutionizing retail with their dynamic pricing B2B SaaS platform, leading the charge in automating and optimizing pricing strategies with AI-driven insights. Their comprehensive solution, embraced by retailers and brands across over 40 markets, delivers actionable pricing recommendations that drive business growth and profitability. Since 2018, they've been empowering a wide range of industries, including consumer electronics, beauty, and apparel, to seamlessly integrate pricing strategies across online and offline channels.

Required skills:

• A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
• 4+ years of professional experience in:
  • End-to-end machine learning lifecycle (design, development, deployment, and monitoring).
  • Advanced Python development, including OOP, writing production-grade code, testing, and optimization.
  • Data mining, statistical analysis, and effective data visualization techniques.
  • Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).
  • Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

Nice-to-Haves:

• Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).
• Experience in reinforcement learning and Monte-Carlo methods.
• A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.
• Experience with cloud services and platforms, preferably AWS.

Scope of work:

As a Data Scientist, you’ll play a critical role in shaping and enhancing our AI-driven pricing platform.
Specifically, you will:
‍

• Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.
• Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.
• Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.

Ми шукаємо Senior Machine Learning Engineer, який буде займатися операціоналізацією моделей комп'ютерного бачення для виявлення, вилучення і класифікації об'єктів.
Ми працюємо над удосконаленням клієнтського інструменту, який дозволяє виявляти продукти на продуктових полицях та надавати додаткові метадані та ознаки.

Чим ви будете займатися у цій ролі

• Перегляд та аналіз існуючих моделей DS, налаштування та їх параметризація за необхідності
• Проєктування, створення, обслуговування, усуннення несправностей та оптимізація повного життєвого циклу машинного навчання, який включає наступне
• Оптимізацію моделі машинного навчання
• Підготовку даних
• Вилучення ознак
• Моніторинг продуктивності моделі
• Співпраця з дослідниками даних та командою інженерів з метою оптимізації продуктивності пайплайнів машинного навчання
• Встановлення і налаштування процесів безперервної інтеграції та розгортання ПЗ
• Безперервне навчання проєктуванню та підтримці моделей машинного навчання
• Надання спроможностей для раннього виявлення різних дрейфів (даних, концепцій, схем тощо)

Навички

• Досвід роботи у якості інженера з машинного навчання або даних за напрямком проєктування, створення та розгортання пайплайнів машинного навчання та обробки даних
• Хороші знання та досвід розробки на Python
• Хороше розуміння екосистеми машинного навчання Python (PyTorch, TensorFlow, NumPy, pandas, sklearn, XGBoost тощо)
• Хороше розуміння концепцій і найкращих практик для ефективного розгортання і підтримки моделей машинного навчання
• Досвід роботи з деякими платформами/технологіями, пов’язаними з практиками для ефективного розгортання і підтримки моделей машинного навчання, такими як AWS SageMaker, Azure ML, GCP Vertex AI / AI Platform, Databricks MLflow, Kubeflow, Airflow, Argo Workflow, TensorFlow Extended (TFX) тощо
• Досвід роботи з базовими інструментами розробки програмного забезпечення, наприклад git, середовищем безперервної інтеграції та розгортання ПЗ (такими як Jenkins або Buildkite), PyPI, Docker, Kubernetes, юніт тестами та об’єктно-орієнтованим проєктуванням в цілому

Our client is a leading SaaS company offering pricing optimization solutions for e-commerce businesses. Its advanced technology utilizes big data, machine learning, and AI to assist customers in optimizing their pricing strategies and maximizing their profits.

About the Role:

As a Data Scientist you’ll play a critical role in shaping and enhancing our AI-driven pricing platform.

Key Responsibilities:

• Develop and Optimize Advanced ML Models: Build, improve, and deploy machine learning and statistical models for forecasting demand, analyzing price elasticities, and recommending optimal pricing strategies.
• Lead End-to-End Data Science Projects: Own your projects fully, from conceptualization and experimentation through production deployment, monitoring, and iterative improvement.
• Innovate with Generative and Predictive AI Solutions: Leverage state-of-the-art generative and predictive modeling techniques to automate complex pricing scenarios and adapt to rapidly changing market dynamics.

Required Competence and Skills:

• A Master’s or PhD in Computer Science, Physics, Applied Mathematics or a related field, demonstrating a strong foundation in analytical thinking.
• At least 5 years of professional experience in end-to-end machine learning lifecycle (design, development, deployment, and monitoring).
• At least 5 years of professional experience with Python development, including OOP, writing production-grade code, testing, and optimization.
• At least 5 years of experience with data mining, statistical analysis, and effective data visualization techniques.
• Deep familiarity with modern ML/DL methods and frameworks (e.g., PyTorch, XGBoost, scikit-learn, statsmodels).
• Strong analytical skills combined with practical experience interpreting model outputs to drive business decisions.

Nice-to-Have:

• Practical knowledge of SQL and experience with large-scale data systems like Hadoop or Spark.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, data version control).
• Experience in reinforcement learning and Monte-Carlo methods.
• A solid grasp of microeconomic principles, including supply and demand dynamics, price elasticity, as well as econometrics.
• Experience with cloud services and platforms, preferably AWS.

Intelliarts is seeking a Machine Learning Engineer to join our growing ML Team.
We are a cross-functional team focused on advancing Intelliarts’ capabilities in the Machine Learning domain. In this role, you’ll collaborate closely with current and prospective clients to explore how ML can address their business challenges – through research, prototyping, and deploying innovative solutions.
You’ll join a team that is currently particularly focused on Large Language Models (LLMs), helping organizations leverage AI to enhance efficiency and automation. Our track record includes building impactful ML-driven applications that have contributed to over $1 billion in client revenue.
This position is ideal for someone with a strong foundation in general machine learning and LLM technologies, excellent problem-solving skills, and the ability to clearly communicate complex technical ideas – particularly to clients based in the USA.

Responsibilities

• Leverage transformer-based models (e.g., GPT, BERT, LLaMA) for domain-specific tasks such as content generation, summarization, and semantic search.
• Build scalable, production-grade RAG pipelines using tools like LangChain, LlamaIndex, or custom frameworks.
• Design and deploy vector search solutions using tools such as FAISS, Qdrant, or Pinecone; optimize dense retrieval pipelines for recall, relevance, and latency.
• Collaborate with DevOps to productionize ML models, ensuring reliability, monitoring, and scalability using cloud infrastructure (AWS preferred).
• Build robust data pipelines to support ML use cases – including indexing, tokenization, and dataset preparation.
• Develop and optimize traditional machine learning models (e.g., tree-based, linear models) for use cases such as classification, regression, ranking, or forecasting.
• Apply best practices in ML model validation, including data splitting strategies (e.g., time-based, stratified), cross-validation, performance tracking, and monitoring in production.
• Work closely with data scientists, software engineers, and product stakeholders to deliver and iterate on ML-based products.

Personal Profile Overview

• Degree in Data Science, Computer Science, Software Engineering or related field
• Stability in previous employment history with a tendency to remain with employers for extended periods
• Experience in managing diverse project activities (not just coding, but also requirements analysis, preparing estimations)
• Clear and effective communication skills, both verbal and written, and ability to convey ideas, information, and messages accurately and efficiently
• Proficiency in fostering effective collaboration and teamwork activities
• Ability to analyze information, assess situations, and make decisions based on sound reasoning and logical evaluation
• Focus on delivering exceptional customer experiences and prioritizing customer satisfaction
• Analytical thinking, problem-solving abilities, and strategic approach to technical challenges
• Transparency in sharing information within a team and company
• Willingness to acquire new knowledge and insights to enhance professional growth and performance

Required skills

• 4+ years of experience in ML or Data Science roles, with at least 1 year focused on LLM or NLP-based systems.
• Hands-on experience with Python and libraries like HuggingFace Transformers, LangChain, PyTorch, TensorFlow, or similar.
• Experience developing and validating classic ML models (e.g., XGBoost, Random Forest, Logistic Regression) for structured or tabular data.
• Strong grasp of model evaluation techniques: precision, recall, ROC-AUC, calibration, error analysis, etc.
• Proven track record of building and deploying ML models into production environments.
• Deep understanding of machine learning algorithms, embeddings, and transformer architectures.
• Solid knowledge of retrieval methods, vector search engines, and hybrid search strategies.
• Familiarity with cloud platforms (AWS strongly preferred), including model hosting, Lambda, S3, or SageMaker.

As a plus

• Experience with fine-tuning large models on custom datasets.
• Knowledge of RAG architectures, search augmentation techniques, and content attribution workflows.
• Experience with prompt engineering, few-shot learning, or alignment techniques.
• Experience designing robust ML pipelines, including model drift detection, retraining workflows, and monitoring systems.
• Familiarity with LLM evaluation methods, hallucination detection, or explainability.
• Understanding of software engineering practices (version control, CI/CD, testing).
• Contributions to open-source AI projects or published work in NLP/LLM areas.

We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

To qualify for the role, you must have

• Minimum 4 years of experience in Data Science and Machine Learning.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Knowledge and experience in Generative AI.
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
• Familiarity with computer vision techniques for image recognition, object detection, or image generation.
• Experience with cloud platforms such as Azure or AWS.
• Expertise in data engineering, including data curation, cleaning, and preprocessing.
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
• Track record of driving innovation and staying updated with the latest AI research and advancements.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Ideally, you’ll also have

• Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems
• Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI
• Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines
• Implement monitoring and logging tools to ensure AI model performance and reliability
• Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
• Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.

Are you looking for a challenging yet rewarding project that will leverage the best of your decision-making and engineering excellence?
At DIAL we strive to maintain a delicate balance between the constantly evolving LLM landscape, the demands and scales of enterprise customers, and the restrictions that come with developing an open-source multimodal LLM and Application Orchestration platform under the Apache 2 license, all while ensuring ease of use and deployment and constantly delivering new features.
Using DIAL as a foundation, we build a variety of practical solutions that can be customized for specific needs, such as StatGPT, a talk-to-your-data platform adopted by the International Monetary Fund and World-Bank. Imagine a future where accessing and understanding complex datasets is as easy as asking a question. With Project StatGPT, that future is now. We're on a mission to democratize data access through the power of Large Language Models (LLMs) based on Natural Language Processing (NLP). StatGPT is designed to bridge the gap between vast data repositories and the business people who need insights from them, using intuitive, conversational interfaces.

Your role:

We see candidate for this position as a mix of a mathematician, algorithm specialist, analyst, and programmer, capable of developing domain expertise and implementing production-ready solutions in most scientifically challenging areas. All the above by either doing comprehensive research or discovering an efficient way of implementing ideas obtained by the research, analytics, or scientific articles.
Here we provide a list of skills and technologies we are interested in. See for yourself, whether any of them are in your scope of expertise or interest. You do not have to master all of them. Tell us what your strong side is and we will find the right task for you. We value the thrive for knowledge and self-development within our team.

Responsibilities

• Design, develop, and maintain core functionalities using Python
• Collaborate with cross-functional teams to define, design, and ship new features
• Ensure the performance, quality, and responsiveness of applications
• Identify and correct bottlenecks and fix bugs
• Help maintain code quality, organization, and automation
• Conduct system and test engineering activities as required

Requirements

• Strong knowledge in common Computer Science and Programming Languages theory
• Good Knowledge of Python
• Understanding of requirements developments. Desire and ability to understand how things work in a specific domain
• Advanced algorithms and data structures

Nice to have

• Knowledge of python libs: Pandas, SciPy, Sklearn, PyTorch, TensorFlow, FastAPI, Streamlit, asyncio and others
• Experience with OpenAI / Langchain / llamaindex / other LLMs - related things
• Experience in Java / C++ / C#
• Experience with Data analytics
• Math, Statistics, Machine learning

We’re seeking a motivated and detail-oriented Data Scientist to join a rapidly growing SaaS company specializing in price optimization for e-commerce. If you enjoy uncovering insights from complex datasets, building predictive models, and solving real-world problems in the e-commerce domain, this role is for you. You’ll work closely with an international team to drive innovation and deliver impactful, data-driven solutions.

Додаткові переваги:

• A dynamic and fast-paced work environment with opportunities for personal and professional growth.
• Flexible working hours and a fully remote position.
• Collaborative and informal team culture that values work-life balance.
• Access to modern tools and equipment of your choice to help you excel in your role.
• Regular team activities, including social events and opportunities to build strong team connections.

Про клієнта:

A leading SaaS company specializing in dynamic pricing and market intelligence solutions for e-commerce businesses. Their platform empowers retailers and brands to monitor competitors' prices, analyze market trends, and optimize pricing strategies in real-time. Its innovative tools provide actionable insights that help businesses increase profitability and maintain a competitive edge. With seamless integrations, customizable dashboards, and automated pricing updates, The company simplifies complex pricing strategies, allowing clients to focus on growth. Trusted by businesses across various industries, it has established itself as a reliable partner in helping companies thrive in the fast-paced world of online retail.

Про проект:

The project centers around one of Denmark’s fastest-growing SaaS companies, dedicated to revolutionizing e-commerce through data-driven solutions. Solutions for the e-commerce industry, enabling businesses to optimize their operations and make strategic decisions. A cutting-edge platform that leverages machine learning, predictive modeling, and data analysis to uncover insights and drive innovation. Collaborating with an international team offers the opportunity to contribute to impactful solutions that shape the future of e-commerce technology.

Вимоги:

• Proficiency in Python and data-focused libraries such as Pandas, Numpy, Scikit-learn, and TensorFlow.
• Strong SQL skills, including experience with complex queries (joins, subqueries, aggregations).
• In-depth understanding of machine learning algorithms and their applications in sales and business data.
• Practical experience in time series analysis for solving business problems like demand forecasting and inventory management.
• Experience deploying and managing machine learning models in a cloud environment (e.g., AWS).
• Expertise in feature engineering and optimization techniques.
• Familiarity with software engineering practices such as version control and testing.
• Experience working with e-commerce sales and customer data will be a plus
• Understanding of e-commerce-specific datasets and their practical applications will be a plus
• Basic knowledge of deep learning methods, particularly LSTMs (Long Short-Term Memory networks) will be a plus

Обов'язки:

• Develop and implement machine learning and deep learning models to address business challenges, including sales forecasting and inventory optimization.
• Conduct advanced time series analysis to identify trends and provide actionable insights.
• Write and optimize complex SQL queries for data extraction, manipulation, and analysis.
• Collaborate with software engineers to integrate predictive models and analytics solutions into the platform.
• Perform exploratory data analysis and present findings to stakeholders and team members.

We’re building a powerful AI platform to drive innovation across all PandaDoc products, and we’re looking for a Sr.Python Engineer who’s passionate about solving real-world challenges with cutting-edge AI technology. This role is for someone who is excited about new emerging Gen AI technologies, thrives in a fast-paced environment, and cares deeply about building systems that deliver real impact to our customers.

What makes this role special?

• Work on a modern AI platform: Build a scalable platform that enables AI-first products at PandaDoc and gives other developers a head start without overcomplexity. Tackle challenges like RAG pipelines, knowledge graphs, LLM routing, fine-tuning, testing, and observability – making it easy for other engineers to integrate and build on top of the platform.
• Tackle real-world challenges: It’s easy to create an impressive demo, but much harder to productize Gen AI applications and make them work reliably for tens of thousands of customers. You will help productize the technology, ensuring it works seamlessly and reliably across all our customers.
• High ownership, fast pace: You’ll have the independence to take projects from 0 to deployment, solving complex problems and delivering results quickly.
• Focus on the end product: Go beyond technical challenges – you’ll build solutions that drive real business value and help small and medium-sized businesses thrive.

What will you do?

• Develop end-to-end systems: Design, build, and deploy web systems and APIs from scratch. You’ll focus on building scalable, reliable solutions that integrate seamlessly with AI tools and workflows.
• Work with modern Gen-AI architecture: Develop pipelines for RAG (retrieval-augmented generation), knowledge graphs, LLM routing, evaluation and testing frameworks, and fine-tuning models for specific use cases.
• Optimize multi-model support: Work with multiple LLMs (like GPT-4, Claude, fine-tuned models) to ensure effective routing, dynamic task handling, and performance optimization.
• Collaborate with product and engineering teams: Partner closely with technical PMs, designers, and other engineers to bring the platform to life and support innovation in AI products.
• Solve real-world AI challenges: Apply your experience working with LLMs to navigate their quirks, troubleshoot issues, and build tools that ensure quality, scalability, and observability.
• Move fast and iterate: Take ownership of your work, ship quickly, and learn from feedback to improve and optimize solutions.

What are we looking for?

• Proficient in Python: 5+ years of experience coding in Python, building web systems, APIs, and scalable backend services.
• Experience with real-world AI applications: You’ve worked on Gen-AI projects, including RAG, knowledge graphs, LLM routing, and fine-tuning. You understand the architecture and tools needed to make these systems work.
• Deep knowledge of LLMs: You’ve worked with multiple LLM models and can explain their quirks, limitations, and how you’ve overcome them in past projects.
• End-to-end development skills: You’ve developed systems from the ground up – from design and coding to deployment and testing.
• Fast pace and high independence: You enjoy working in a fast-moving environment with lots of autonomy to solve problems and deliver results.
• Product-focused mindset: You care about the impact of your work and strive to build systems that deliver tangible value to customers.

Necessary skills and qualifications

• At least 4 years of experience deploying and managing ML models with a strong understanding of AI/ML lifecycle management, automation tools, and version control systems (e.g., Git)
• Experience with deploying open-source Large Language Models (LLMs)
• Proficiency with ML Ops for assessing and monitoring model performance and scalability
• Familiarity with Python, and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines/ Azure ML Studio/ VertexAI)
• Expertise in deploying models on cloud platforms such as AWS, Azure, or GCP
• Good knowledge of machine learning and deep learning principles
• Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams
• Upper-intermediate level of English proficiency

Will be a plus

• Experience with Kubernetes
• Familiarity with Retrieval-Augmented Generation (RAG) pipelines
• Knowledge and experience in API development

Responsibilities

• Develop, refine, and use ML engineering platforms and components, development workflow pipelines
• Deployment of open-source LLMs and other models to different instances
• Collaborate closely with client-facing teams to understand their needs and provide technical support
• Rapid model deployment implementation
• Developing process-related documentation
• Kubeflow and MLFlow upgrade