Hire Machine learning Engineer

* Machine Learning Engineer with over six years of experience in AI and machine learning. * Specializes in recommendation systems, predictive analytics, and computer vision solutions. * Experience with predictive models for demand forecasting and property valuation, optimizing inventory and decision-making processes.

Results-driven AI/ML Engineer who transforms data into actionable business insights. Led development of recommendation systems that increased user engagement by 35% and fraud detection models that reduced financial losses by $2M annually. Expert in building scalable ML infrastructure and cross-functional collaboration, with experience managing full ML lifecycle from research to production deployment. Combines strong technical expertise in Python, PyTorch, and cloud technologies with business acumen to deliver measurable ROI through AI solutions.

- Over 15 years experience in leading the design, developing, and delivery of complex IT projects and high-performance solutions, +10 years in business intelligence and in the data analytics field - Advanced hands-on experience in reactive, microservices-based, distributed system design and development including stream application platforms for advanced analytics including machine learning and data science - Proficient Data Engineer-researcher focused on the immediate benefits for the business using Big Data tools (AWS Glue, AWS Greengrass, AWS EMR, AWS Data Lake) with advanced analytical and visualization APIs (graph DB – Titan, Neo4J, Tinkerpop, software development – Scala, Python) with CI/CD pipelines – Jenkins, Circle CI, GitLab actions - Generative AI - Q&A with multiple choices, pre-trained models (Hugging Faces ecosystem, T5, BERT, GPT), ChatBot for online gambling platform (LangChain, Pinecone, Cohere, Faiss, Hugging Face Hub) - Generative AI in NLP - information retrieval for 1) generate personalized recommendations for products or services based on a user's preferences and past behavior 2) summarize legal documents and contracts, making it easier for lawyers and legal professionals to review and analyze large volumes of legal documents. 3) create content such as product descriptions, blog posts, and social media posts - Recommendations platforms - mobile games platform (generate game recommendations based on player history, promo-offers, AWS Personalize ), self-learning algorithms for data-based risk management in agriculture (Monte-Carlo tree and Markov chains) - Upper-intermediate English. - Availability starting from ASAP

- Applied data scientist and MLOps engineer with 5+ years in PHY security and ML for wireless systems. - End-to-end ML delivery: data wrangling, feature engineering, model development (scikit-learn, PyTorch), evaluation, and CI-friendly deployment. - Built ML-driven performance measurement and scheduling/optimization services; exposed via REST APIs; productionized on Microsoft Azure (ML Studio, Function Apps). - Strong data engineering foundation: SQL modeling and queries (Azure Data Studio), data pipelines, and reproducible experimentation. - Methods expertise: supervised/unsupervised learning, reinforcement learning, adversarial/robust modeling, optimization techniques. - Practical MLOps: containerized services, API design, monitoring-oriented deployment patterns, version control (Git). - Domain background: physical-layer authentication, anti-jamming/anti-spoofing, and federated/edge learning research. - Track record of translating complex problem statements into scalable, measurable data products with clear product impact.

Data Science engineer with over 3 years of practical commercial experience in Natural Language Processing (NLP), Computer Vision (CV), and Recommender Systems. Available skills in data analysis using machine learning approaches to satisfy business needs, problem-solving, and other tasks in this sphere. A person, focused on obtaining the best results, using all knowledge and skills. Friendly and ready to help the team complete tasks and solve certain problems.

Certified Data Scientist bringing an 3+ year commercial expertise, particularly in NLP, CV, and 3D modeling, underpinned by a solid foundation in machine learning and data processing. Commands an advanced proficiency in Python, complemented by adeptness in JavaScript and NodeJS. Demonstrates in-depth experience with Python libraries such as Pandas, numpy, and PyTorch, and excels in deploying solutions with Git, Docker and API development. Proven track record in industries such as SEO and logistics, leveraging statistical models and ML solutions to drive data insights and optimization. Renowned for transforming complex requirements into scalable algorithms and models, with academic credentials in Mechanical and Computer Engineering.

Ivan is a Lead Kotlin/Java Engineer with solid experience in backend and Android development. He builds reliable and maintainable applications, works well with cross-functional teams, and enjoys improving codebases and system architecture. Ivan is comfortable mentoring others and contributing to both mobile and backend projects, making sure they run smoothly and efficiently.- Software Engineer with 5+ years of experience in developing Android and backend solutions in the healthcare, fitness, and automotive industries; - Strong Skills with Kotlin, Java, and TypeScript, creating Android applications on Jetpack Compose, Firebase, Android SDK, KMM, as well as backend solutions on Spring Boot (and basic experience with Node.js / React for integrations and prototypes); - Experienced with AWS (Serverless, Lambda, S3, API Gateway) and GCP, builds cloud infrastructure, and is undergoing Google Cloud certification; - Skilled with Firebase as a backend platform; - Experience CI/CD, Docker, GitHub Actions, works according to Agile principles; - Interested in implementing AI models in production solutions.

- Senior Python/ML Engineer with 10+ years in IT and 8+ years of professional Python experience; - Experienced in API and backend development with Python, data processing using Pandas/NumPy, and automation scripting; - Deep SQL expertise, including query optimization and database operations; - Experience with Apache Airflow, Apache Kafka, and Apache Spark/PySpark for data processing and workflow orchestration; - Strong Skills in ML/NLP frameworks such as TensorFlow, PyTorch, BERT, NLTK, and spaCy; - Extensive AWS experience (S3, Athena, EMR, Redshift, SageMaker) and Kubernetes for scalable deployments; - Built and deployed end-to-end ML pipelines and integrated AI solutions into business workflows; - Leadership as an ML engineering team lead.