Jobs

⚡️ Architect / Senior Databricks Engineer (Databricks Certified)

We are looking for an experienced Architect / Senior Databricks Engineer to join a long-term, full-time project currently in the pre-sale stage.

This is a high-priority opportunity, and we are seeking a strong technical leader with proven expertise in Apache Spark and Databricks, capable of designing and implementing scalable big data solutions while effectively collaborating with technical teams and business stakeholders.

Requirements:

Extensive hands-on experience with Apache Spark

Proven experience working with Databricks across multiple large-scale projects

Databricks Certified Data Engineer Professional certification

Strong background in big data technologies, including Hadoop, NoSQL, MPP, OLTP, OLAP

7+ years of experience as a Software Engineer or Data Engineer, including:

Query tuning and performance optimization

Troubleshooting and debugging Spark or other big data solutions

Proficiency in Python, Scala, or Java programming

Practical experience designing and deploying solutions on cloud platforms (AWS, Azure, or GCP)

Familiarity with CI/CD tools, unit and integration testing, automation, orchestration, REST APIs, BI tools, and SQL interfaces (e.g., Jenkins)

Excellent communication and presentation skills, with the ability to engage strategic stakeholders and leadership

Experience in customer-facing roles, such as pre-sales, post-sales, technical architecture guidance, or consulting

Passion for continuous learning and ensuring customer success

Nice to Have:

Experience in Data Science / ML Engineering, including:

Model selection and lifecycle management

Hyper-parameter tuning

Model serving and deep learning

Working with tools such as MLFlow

Responsibilities:

Design, implement, and optimize data architecture and big data solutions

Lead the adoption and scaling of Databricks within the project

Collaborate with data engineers, data scientists, and business stakeholders to define technical strategies

Ensure performance, scalability, and reliability of data pipelines and analytics platforms

Provide technical leadership, mentoring, and guidance to team members

Engage with stakeholders and customers to gather requirements and deliver strategic solutions

Stay up-to-date with emerging trends and innovations in big data and Databricks technologies

Recruitment Process:

Recruiter interview

Technical interview

Client interview

Offer

Apply now and help shape this project from the very beginning! 🚀

The UKEESS Software House team is currently looking for a Senior AI LLM Data Scientist / Engineer to join our team for a full-time position (remotely in Ukraine or in Lviv’s office).

About the Customer and the Project:

Our customer is the world’s largest DNA network, based in the USA. This presents a unique opportunity to work with more than 60 billion digitized global historical records, 100 million family trees, and 18+ million people in their growing database. Our customers help people discover their family stories and gain actionable insights about their health and wellness. 

About the team:

You will join the AI Content team, a dynamic group at the forefront of Document Understanding. You’ll play a vital role in developing innovative AI models that extract and organize text and image information from billions of historical and genealogical records, enabling customers to discover, share, and connect with their family history. 

As a member of the AI Content team, you will work with AI technologies and LLMs to deploy, test, and evaluate model capabilities, quality, throughput, and cost for document understanding tasks such as layout analysis, transcription, entity recognition, relation extraction, summarization, etc. You will work with a dedicated mentor on the AI Content data science team, along with engineering teams, to train, optimize, and deploy models that promote product development, customer success, and content creation across our project.

What you will do:

• Integrate LLMs: Integrate both open source and provider-based LLMs into our internal AI Gateway. 
• LLM Optimization: Optimizing open source LLMs for faster inference using frameworks like VLLM, SGLang
• Tools/Scripts/Dashboards: build a tool/script/dashboard to track and compare speed or time required, as well as token count and cost estimates for processing images with the various LLMs.  
• Optional Opportunities: Optional opportunities exist to explore LLM word token bounding box detection, LLM as a Judge, and other LLM evaluation work. 
• Collaborate on Cloud Deployment: Partner closely with ML Ops and Data Science Engineers to seamlessly deploy datasets, truth sets, models, and pipelines for training and inference in cloud environments.
• Communicate Insights Effectively: Clearly and confidently present your findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives.

Requirements:

• 5+ years of experience in Data Science with AI/ML 
• Proven experience in Python programming as well as tools and environments for model deployment.
• Knowledge and experience with multiple AI LLMs, including both proprietary and open-source models, and their respective strengths and limitations.  
• Knowledge and experience with such frameworks as VLLM, SGLang
• Ability to stay up-to-date with new models, benchmarks, and best practices.
• Practical experience with cloud platform AWS (e.g. Amazon SageMaker, EC2, S3, AWS Lambda).
• English: Upper-intermediate at least (both spoken and written)

It will be a plus:  

• Familiarity with cloud platforms and related AI/ML services such as Google GCP Gemini API, Vertex AI, Azure, etc.  
• Commercial experience with Terraform or CloudFormation
• Experience with agentic architecture
• Familiarity with AI coding tools 

What You’ll Gain

• Mentorship & Growth: Learn from experienced Data Scientists while tackling meaningful, real-world AI projects, expanding your knowledge and professional network within a collaborative culture. 
• Collaboration & Impact: Work alongside top industry professionals and help shape the tools that bring family history to life for millions of users.
• Innovation & Purpose: Join a team at the forefront of applying AI to historical data - where every model you build helps preserve human stories.

What do we offer our new colleague?

• Competitive compensation (based on market data, but also depending on the technical level of the candidate)
• Flexible work schedule
• 3 health packages to choose
• Annual paid vacation and state holiday celebration
• Free English classes (online)
• Individual approach to professional growth
• Lack of bureaucracy and micromanagement
• Modern, comfortable office facilities (a barbecue zone, kitchens, lounge rooms, coffee machines, etc.)
• Foreign business trips (after the war)
• On-site parking lot and charge station for Electric Cars
• Corporate gifts, celebrations, and fun activities

• Sports activities: ping-pong, soccer, work-out

   

Suppose you have a passion for solving challenging problems, building scalable, robust systems, love working with the latest technologies in a fast-paced, flexible environment, and are excited about the prospect of having a significant impact on products with more than 3 million paying subscribers. In that case, we want to talk to you! ;-)

The UKEESS Software House team is currently looking for a Senior AI Data Scientist / Engineer to join our team for a full-time position (remotely in Ukraine or in Lviv’s office).

About the Customer and the Project:

Our customer is the world’s largest DNA network, based in the USA. This presents a unique opportunity to work with more than 60 billion digitized global historical records, 100 million family trees, and 18+ million people in their growing database. Our customers help people discover their family stories and gain actionable insights about their health and wellness. 

About the team:

You will join the AI Content team, a dynamic group at the forefront of Document Understanding. You’ll play a vital role in developing innovative AI models that extract and organize text and image information from billions of historical and genealogical records, enabling customers to discover, share, and connect with their family history. 

As a member of the team, you will work with KB (Knowledge Base) and RAG (Retrieval Augmented Generation) implementations, integrating architectures leveraging SQL-structured databases along with vector databases supporting semantic search and retrieval applications. You will work with a dedicated mentor from the data science team, as well as engineering teams, to train, optimize, and deploy models that promote product development, customer success, and content creation across our project.

What you will do:

• Configure structured and vector databases: Align and sync database schemas across structured and vector databases 
• Curate and organize content collection metadata: Prepare and format provided content collection metadata to be compatible with defined database schemas 
• Ingest content collection metadata:  Ingest collection metadata from provided sources into a structured SQL database.
• Embeddings generation: Help develop a tool/script to generate embeddings from the structured data to populate the vector database.
• Iterative improvement: Iterate on adjusting the database schema, indexes, embeddings, etc., to support various queries and use cases for analyzing the ingested content collection metadata
• Collaborate on Cloud Deployment: Partner closely with ML Ops and Data Science Engineers to seamlessly deploy datasets, truth sets, models, and pipelines for training and inference in cloud environments.
• Communicate Insights Effectively: Clearly and confidently present your findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives.

Requirements:

• 5+ years of experience in Data Science
• Strong hands-on commercial experience with LLMs in production, RAG architecture, and agentic systems
• Expertise with data collection, organization, curation, and formatting to populate SQL databases. 
• Experience with SQL databases, including adjusting schemas and indices to optimize for efficient queries. 
• Familiar with embedding generation and use of vector databases for semantic search and retrieval. 
• Strong proficiency and experience with Python and relevant tools and libraries
• Practical experience with cloud platform AWS (e.g. Amazon SageMaker, EC2, S3, AWS Lambda).
• English: Upper-intermediate at least (both spoken and written)

It will be a plus:

• Knowledge and experience with cloud platforms and related AI/ML services such as Google GCP Gemini API, Vertex AI, Azure, etc.  
• Strong knowledge and experience with LightLLM
• Commercial experience with Terraform or CloudFormation
• Experience with agentic web scraping tools

What You’ll Gain

• Mentorship & Growth: Learn from experienced Data Scientists while tackling meaningful, real-world AI projects, expanding your knowledge and professional network within a collaborative culture. 
• Collaboration & Impact: Work alongside top industry professionals and help shape the tools that bring family history to life for millions of users.
• Innovation & Purpose: Join a team at the forefront of applying AI to historical data - where every model you build helps preserve human stories.

What do we offer our new colleague?

• Competitive compensation (based on market data but also depending on the technical level of the candidate)
• Flexible work schedule
• 3 health packages to choose
• Annual paid vacation and state holiday celebration
• Free English classes (online)
• Individual approach to professional growth
• Lack of bureaucracy and micromanagement
• Modern, comfortable office facilities (a barbecue zone, kitchens, lounge rooms, coffee machines, etc.)
• Foreign business trips (after the war)
• On-site parking lot and charge station for Electric Cars
• Corporate gifts, celebrations, and fun activities

• Sports activities: ping-pong, soccer, work-out

   

Suppose you have a passion for solving challenging problems, building scalable, robust systems, love working with the latest technologies in a fast-paced, flexible environment, and are excited about the prospect of having a significant impact on products with more than 3 million paying subscribers.

In that case, we want to talk to you! ;-)

Hello! We’re looking for a motivated and tech-savvy Junior AI Specialist to support our work on intelligent AI-driven systems. From smart chats and LLM prompt design to autonomous AI agents and process automation — you’ll get hands-on experience building tools that solve real-world business challenges.

 

Key responsibilities:

• Building and testing AI agents for lead research, client outreach, and pipeline management;
• Designing and refining prompts for Large Language Models (LLMs) to improve conversation quality and task performance;
• Automating business processes using n8n — integrating databases, scraping tools, and outreach platforms;
• Developing lightweight chatbots and conversational flows for use in marketing or support;
• Supporting data collection and processing to enable targeted outbound campaigns;
• Collaborating with team members to improve AI-driven workflows and propose better strategies.
   

Requirements:

• Solid interest in AI, LLMs, and workflow automation;
• Basic experience with tools like OpenAI, or agent frameworks;
• Basic understanding of JavaScript/TypeScript and willingness to improve skills through practical application. 
• Practical understanding of n8n — or strong motivation to learn it quickly (experience building flows, connecting APIs, etc.);
• Strong problem-solving skills and the ability to independently conduct online research and experimentation;
• Upper-intermediate level of English (written and verbal);
• A self-starter with a learning mindset — not afraid to test, iterate, and improve.
   

What you will have with us:

• Regular Performance review;
• Paid out-of-office days;
• Opportunity to learn and improve your English.
• Flexible work schedule;
• Well-equipped office;
• Career Path and growth opportunities.

About company

We are a software development company that provides digital technology services from mobile and web development to custom software solutions. We're dedicated to delivering innovative, high-quality solutions tailored to your unique needs.

N.B! Locations  -  remote from Latvia, Lithuania, Spain, Portugal

We are looking for a highly skilled Senior Machine Learning Engineer to design, develop, and deliver production-ready ML solutions. The ideal candidate will combine deep technical expertise with strong communication and collaboration skills, capable of working independently while driving end-to-end model development and deployment.

Key Responsibilities:
Design, build, and deploy production-grade ML models and pipelines using Python.
Translate business requirements into scalable and efficient ML solutions.
Work independently to own the full model lifecycle — from data exploration to production delivery and monitoring.
Collaborate closely with cross-functional teams, including data scientists, engineers, and product stakeholders.
Communicate complex ML concepts and insights clearly to non-technical audiences.
Optimize and deploy models using AWS infrastructure and related cloud services.

Required Skills and Qualifications:
10+ years of experience in Machine Learning, Data Science, or related fields.
Expert-level proficiency in Python, including production-grade software development practices.
Proven experience deploying ML models in production environments.
Strong understanding of ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and modern MLOps practices.
Excellent collaboration and communication skills.
Hands-on experience with AWS services for ML (e.g., SageMaker, Lambda, S3, ECS, or EC2).
Nice to Have:

Experience with CI/CD for ML workflows.
Familiarity with containerization (Docker, Kubernetes).
Background in data engineering or large-scale distributed systems.

About the project:

We are building a corporate AI Assistant powered by Microsoft Azure and OpenAI technologies. The system helps employees search, analyze, and generate internal documents. The long-term goal is to extend AI Assistant capabilities across all company departments.

To strengthen our team, we are looking for an experienced ML Architect (Azure AI / RAG) who will design and implement the machine learning architecture, integrate AI models, and ensure production-level performance and reliability.

Responsibilities:

• Design and implement AI architecture on Microsoft Azure (Azure ML, Cognitive Search, OpenAI, Databricks). 
• Build and manage RAG pipelines (Retrieval-Augmented Generation) and vector search systems. 
• Develop and optimize ML pipelines for embeddings, data preprocessing, and model evaluation. 
• Collaborate with DevOps and Data Engineer teams to ensure seamless integration and deployment. 
• Establish and maintain MLOps practices (model versioning, evaluation, monitoring). 
• Define and track AI performance metrics (latency, precision, recall, cost per request). 
• Create documentation (ADR, architecture diagrams, experiment tracking).

Requirements:

• 3+ years of experience in Machine Learning / AI / Data Engineering. 
• Strong background with Microsoft Azure ML / Cognitive Search / Databricks / OpenAI. 
• Proficiency in Python, FastAPI, LangChain / LlamaIndex, MLflow, Airflow. 
• Hands-on experience with vector databases (FAISS, Pinecone, pgvector, Cognitive Search). 
• Understanding of RAG, embeddings, prompt optimization, LLM orchestration. 
• Experience building MLOps / CI-CD for ML models in production. 
• English — Upper-Intermediate+ (for documentation and collaboration).

Will be a plus:

• Experience with Azure OpenAI Service, Azure Document Intelligence. 
• Knowledge of data governance, PII protection, cost optimization. 
• Background in AI-driven enterprise automation or corporate assistants.

We offer:

• Opportunity to design a core AI architecture from scratch and influence all key technical decisions. 
• Participation in a high-impact AI transformation project that scales across multiple departments. 
• Remote or hybrid work format, flexible schedule. 
• Transparent B2B / contract cooperation. 
• Supportive and technically strong team (DevOps, Data, Product).

How to apply:

Send your CV.
We will contact you shortly.

We’re working in one of the most important sectors for the global economy: maritime shipping. 

Nearly every person is affected by stuff shipping on the seas, whether it’s energy, raw ore, or wind turbines.   But the industry itself is antiquated and archaic, it’s hampered by paperwork and bureaucracy. 

This role sits with our Product Engineering team and involves shipping AI and ML features into production, maintaining those features and models, and working on new models.  You'll be working with and as software engineers to bring models to life for our customers, and also developing prototypes for new features to productionize as well. The types of features are quite broad, but largely fall into three different buckets:

1. "Classical" machine learning - building models and training regressors and classifiers for use in production, including cleaning training data, evaluating and comparing model performance, and monitoring in production.
2. LLMs - using generative AI and LLMs to create agentic workflows for our customers.
3. Statistical modeling - coming up with models that have probabilistic outcomes and confidence intervals related to maritime shipping.

The work might range from reading and comparing documents in multiple languages, classifying entities in image recognition, or even predicting ship operation times. If you’re the sort of person who is intellectually curious, likes statistics, and is excited to put ML and AI models into production then we’d like to hear from you.

Requirements

• Intellectual curiosity and interest in maritime shipping.
• Desire to talk to and get close to customers, end users, developers, designers, product managers, and other stakeholders.
• Minimum 3 years experience in using Scikit-learn and Tensorflow or PyTorth in production.
• Experience using OpenAI or other APIs for LLMs in production.
• Experience in Software Engineering in Python or Typescript.
• Strong knowledge of SQL.
• Strong understanding of statistics.
• Proficiency with CI/CD tools, git, and modern development workflows.
• Experience with AWS, and containerized environments (e.g. Docker, Kubernetes)
• Fluency in English and strong written and verbal communication.
• Excellent analytic skills and attention to detail.

Boosty Labs is a trusted blockchain development partner for over 150 clients worldwide including industry leaders and Fortune 500 companies. Our technical expertise spans Golang, Rust, Solidity, Javascript, Typescript, Python, Node.js, React.js, Vue.js, Flutter, Swift, and Kotlin — everything needed to build robust blockchain and fintech solutions from the ground up. 

We are looking for Blockchain Research Scientist with 4+ years of research experience in cryptography, blockchain protocols, or distributed systems, with a strong academic background (PhD preferred or equivalent industry research experience)

Requirements:

• Cryptography - Deep knowledge of zero-knowledge proofs, SNARKs, STARKs, and advanced cryptographic protocols
• Blockchain Theory - Expertise in consensus mechanisms, game theory, and economic security models
• Zero-Knowledge Systems - Research experience in ZK proof systems, circuit optimization, and zkVM design
• Protocol Design - Ability to design and analyze novel blockchain protocols and Layer 2 solutions

Technical Skills:

• Proficiency in formal mathematical proofs and security analysis
• Experience with cryptographic libraries and ZK frameworks (Circom, Halo2, Plonky2, etc.)
• Programming skills in Rust, Python, or similar languages for prototyping
• Understanding of complexity theory and algorithm design
• Familiarity with formal verification tools

Academic Background:

• Publications 
• Strong foundation in mathematics, computer science, or related fields
• Experience with peer review process and academic collaboration

Nice to Have:

• Research in MEV, cross-chain protocols, or privacy-preserving technologies
• Experience with economic mechanism design
• Knowledge of quantum-resistant cryptography

• Background in formal methods and verification

  Research & Innovation:

• Conduct cutting-edge research in zero-knowledge proofs, consensus mechanisms, and blockchain scalability
• Design novel cryptographic protocols and prove their security properties
• Analyze and improve existing protocol designs for performance and security
• Explore new applications of ZK technology in blockchain systems

• Investigate economic incentive mechanisms and game-theoretic aspects of protocols

  Technical Output:

• Publish research findings in academic conferences and technical blogs
• Write formal specifications and security proofs for new protocols
• Create prototypes and proof-of-concepts to validate research ideas

• Contribute to protocol improvement proposals and technical standards

  Collaboration:

• Work closely with engineering teams to implement research findings
• Review and provide feedback on protocol designs and implementations
• Present research findings to internal teams and external audiences
• Collaborate with external researchers and academic institutions

• What we offer: 
• Flexible working format (remote)
• Flexible working hours
• Informal and friendly atmosphere
• The ability to focus on your work: minimized bureaucracy and micromanagement
• 20 paid vacation days
• Mentorship & Assistance within the team
• 7 paid sick leaves
• Education reimbursement
• Free English classes

• On-Demand Psychologist consultations

   

This role emphasizes a balanced blend of AI innovation and robust backend engineering, with a strong focus on Python for scalable, AI-integrated systems—particularly RAG-enhanced LLMs for reliable, context-aware applications. We're seeking an engineer who thrives on integrating RAG and LLMs to solve real challenges.

Skills and Experience:

• 1+ years of hands-on experience in AI development, with a focus on generative AI, large language models (LLMs), and Retrieval-Augmented Generation (RAG) systems.
• Strong backend skills in Python (this is a must), including proficiency in frameworks like FastAPI or Django for building scalable APIs and services, along with async programming using asyncio for high-performance applications.
• Deep experience with leading LLMs and APIs, including OpenAI, Grok, Gemini, Claude, DeepSeek, Llama, and Mistral, with practical application in RAG pipelines for enhanced retrieval and generation.
• Proficiency in prompt engineering for effective LLM interactions, output optimization, and RAG-specific techniques like query rewriting and reranking.
• Able to quickly learn and adapt to new models, tools, and APIs.
• Experience testing, debugging, and monitoring AI pipelines and models, including observability tools for performance tracking in RAG and LLM workflows.
• Experience in data cleaning, preparation, and sanitization, and data privacy in preprocessing; familiarity with Python libraries like Pandas and NumPy for data handling in LLM and RAG contexts.
• Excellent communication skills, collaboration, and problem-solving abilities, with a team-oriented mindset.

Nice to have:

• Advanced knowledge of frameworks like LangChain, Haystack, or LlamaIndex for building sophisticated RAG systems, including vector databases (e.g., Pinecone or Weaviate), and hybrid search.
• Understanding of sustainable AI practices, multimodal AI (e.g., handling text, image, and audio inputs with LLMs).
• Knowledge of caching (e.g., Redis), and security best practices (e.g., OAuth, JWT) for Python backends.

Responsibilities:

• Write clean, and well-documented code with an emphasis on security, maintainability, and testing (e.g., pytest for Python).
• Develop and integrate AI features into backend applications.
• Assist with data analysis, visualizations, and reporting.
• Collaborate closely with the backend engineering team.

We offer:

• Work in an innovative team and friendly atmosphere.
• Flexible working hours and remote-friendly options.
• Opportunity to work with cutting-edge AI models and technologies in real-world projects.

Join our partner to build the ML systems that power actionable insights for investors everywhere. 
 

What you’ll do

• Design, train, and evaluate ML/DL models (with a strong emphasis on classical ML where appropriate) for ranking, prediction, and risk/quality signals.
• Productionize models end-to-end: data pipelines, feature stores, deployment, scaling, monitoring, and optimization.
• Collaborate with product, research, and engineering to translate financial problems into measurable ML solutions.
• Own experiment design, metrics, and A/B testing; communicate findings clearly to technical and non-technical stakeholders.

• Contribute to model governance, reproducibility, and documentation across the ML lifecycle.

   

What you’ll bring

• MS or PhD in Computer Science, Data Science, AI, or a related quantitative field.
• 4+ years building and shipping ML/DL models in production (with depth in classical ML methods).
• Expert coding in Python; hands-on with PyTorch and/or TensorFlow and common DL libraries.
• Strong foundations in linear algebra, calculus, statistics, and probability.
• Solid grasp of algorithms and data structures.
• Proficiency with Pandas, scikit-learn, and the broader Python data stack.
• Experience with model deployment, optimization, scaling, and serving.
• Excellent problem-solving, analytical, and quantitative skills.
• Hands-on experience delivering solutions in the financial domain.

• Clear, concise communicator and a collaborative team player.

   

Nice to have

• Research or applied experience in LLMs/NLP and modern machine learning.
• Work with multi-modal data (e.g., text, tabular/market data, images, audio).
• Familiarity with AWS or GCP for large-scale training/inference.
• Understanding of MLOps and production ML workflows (CI/CD for models, monitoring, model/data versioning).
• Background in information retrieval, knowledge graphs, or reasoning.

External Tech Expert (On Demand)

remote

We’re looking for an experienced AI/ML Solutions expert with an Architect-level experience, specifically with inventory demand forecasting models experience to help us with our existing projects now and other projects in the future as well.

We need a part-time tech expert: up to 20 hours per week.

More information about us — [meet INSART]

Role Responsibilities 👨‍💻

• Actively participate in pre-sales discussions with potential clients, demonstrating expertise in AI/ML solutions.
• Create proof-of-concept models and demonstrations to showcase the value of AI/ML in solving client challenges.
• Provide input on proposals and pitches to win new business.
• Design AI/ML models and algorithms that align with client goals, ensuring scalability and robustness
• Analyze client data and operational processes to identify opportunities for AI/ML integration

Skill set and experience we believe you should have for that role 🤓

• Proven Experience with inventory demand forecasting models
• Proven experience designing and deploying AI/ML solutions used by end clients and real users.
• Strong understanding of machine learning algorithms, data analysis, and AI architecture.
• Proficiency with AI/ML frameworks such as TensorFlow, PyTorch, or similar.
• Solid programming skills in Python, R, or similar languages.
• Ability to work with large datasets, leveraging tools like SQL, NoSQL, and data pipelines.
• Experience in preparing technical documentation, estimates, and action plans for implementation.
• Exceptional verbal and written communication skills, with the ability to explain complex AI/ML concepts to non-technical audiences.
• Prior experience working with both existing clients and supporting pre-sales efforts in a service-oriented company
• Experience in the fintech domain is highly desirable
• Excellent communication skills (English C1)

Interview Stages:

• Intro call with Recruiter (up to 45 minutes)
• Interview with Head of Software Delivery (up to 60 minutes)

What sets us apart?
Here are just a few reasons why this position is a standout opportunity:

🚀 Opportunity for Growth: As part of our dynamic and fast-growing team, you’ll have the chance to make a real impact and grow your career in exciting new directions.

🌍 Remote Mode: You can have a fully comfortable mode, just stick to deadlines and attend team meetings.

🕰️ Flexible Schedule: Our cooperation will not have an impact on the work-life balance — this is the most important thing for us. In INSART we are committed to making cooperation enjoyable and comfortable first.

💡 Innovation: We’re constantly pushing the boundaries of what’s possible, so you’ll have the chance to join cutting-edge projects and technologies.

👩‍💻 Diversity and Inclusion: We believe that diversity and inclusion are essential to building a strong and successful team. We welcome people of all backgrounds and experiences to join us.

👥 Collaborative Environment: You’ll stay closely with our talented developers to ensure that our products and features are thoroughly tested and of the highest quality.

📚 Free Learning: We believe in continuous learning and development, so we provide free access to a variety of online learning resources to help you stay up-to-date with the latest technologies and industry trends.

Join us!

Our youtube channel: youtu.be/4sTbBCsAFRQ

Looking forward to having a mutually interesting conversation with you! 😉

We’re looking for an ML Engineer who can take ownership of end-to-end model development from data exploration and analysis to modelling, optimization and deployment.

In addition to classic ML solutions, this role will also contribute to research and prototyping around LLMs, embeddings, and AI agents, helping us explore new ways of bringing intelligence into products and workflows.

Responsibilities:
 

• Develop and improve machine learning models for classic solutions such as regression, classification, time-series forecasting, etc
• Conduct data analysis and model evaluation to extract actionable insights.
• Design and maintain data pipelines for model training, validation, and deployment.
• Implement and optimize ML workflows.
• Build AI agents and voice assistants combining LLMs, STT, and TTS systems.
• Research and apply new techniques for data processing, modelling and GenAI solutions.

Requirements:
 

• 2-3 years of commercial experience as an ML Engineer or Data Scientist.
• Strong proficiency with Python and data processing and analysis technologies (pandas, numpy, scipy, spark, seaborn, etc.).
• Solid understanding of classic machine learning algorithms
• Good knowledge of neural networks (PyTorch or TensorFlow).
• Hands-on experience with databases (SQL, PostgreSQL).
• Understanding of RAG architectures and context retrieval systems.
• Experience working with LLMs (fine-tuning, embeddings, prompt engineering).
• Practical experience with cloud platforms (AWS, GCP, or Azure).
• Upper-intermediate level of English (B2)

Special bonuses for you:
 

• Remote-first and flexible work with optional co‑working spaces
• Performance-based bonuses and tax coverage 
• Competitive vacation policy and local holidays for real work-life balance
• Professional development support courses, certifications, and conferences covered
  
  
   

We're looking for a MLOps Engineer to join a high-impact healthcare initiative with our client, a world-renowned leader in medical technology. You’ll be part of a team driving the cloud migration of a secure digital surgical ecosystem from Azure to AWS.

This platform is at the heart of a next-generation surgical experience, connecting data, devices, and teams to power advanced analytics and machine learning models. You will be responsible for building, automating, and maintaining the infrastructure that supports the entire machine learning lifecycle, from data ingestion to model deployment and monitoring. In this role, you'll help build a secure, resilient, and compliant environment for critical healthcare applications that leverage AI and machine learning.

 

Required Skills

• MLOps Expertise: Proven experience in building and managing machine learning pipelines in a production environment.
• AWS Expertise: Extensive hands-on experience with core AWS services (S3, SageMaker, EKS, Lambda, CloudFormation, etc.).
• DevOps Practices: Deep understanding of CI/CD, automation, and infrastructure as code (IaC) using Terraform or CloudFormation.
• Containerization: Solid experience with Docker and Kubernetes for orchestrating ML workloads.
• Scripting: Proficiency in Python and other scripting languages for automation.
• Data Engineering: Familiarity with data processing workflows and tools for handling large datasets.

Nice-to-Have Skills

• Media Experience: Experience with AWS Media Services (e.g., AWS Elemental, Kinesis Video Streams) or a background in managing video data.
• Surgical/Medical Context: Prior experience with medical devices, DICOM standards, or healthcare data is a plus.
• Machine Learning Frameworks: Familiarity with frameworks like TensorFlow, PyTorch, or scikit-learn.

Job Responsibilities

This is your chance to work on a product that impacts lives, leverages modern cloud technology, and prioritizes security, performance, and reliability.

Key Responsibilities

• Design and implement MLOps pipelines for the training, testing, and deployment of machine learning models on AWS.
• Automate the end-to-end machine learning lifecycle, including data versioning, model training, and continuous integration/continuous delivery (CI/CD) for model updates.
• Manage and optimize the cloud infrastructure on AWS to ensure scalable and cost-effective model serving and inference.
• Collaborate with data scientists and machine learning engineers to streamline the transition of models from development to production.
• Establish robust monitoring and logging for model performance, data drift, and system health in a production environment.
• Ensure the security and compliance of the ML platform, adhering to healthcare industry standards.
• Provide technical leadership and guidance on MLOps best practices, tools, and workflows.
   

Department/Project Description

Join us to build the connected vision intelligence layer that unifies surgical imaging, robotics, and data services across the operating room portfolio spanning endoluminal, orthopedics, and the next-gen general-surgery platform, while powering the digital ecosystem in hospitals. You’ll help transform raw surgical video and device signals into real-time insights, collaborative telepresence, and longitudinal case intelligence used before, during, and after procedures. First product releases include surgical video editing/publishing and telepresence, rolling out to select sites in the near future. Your work will directly accelerate that journey and connect robotic vision to the OR and hospital digital platform

This platform is at the heart of a next-generation surgical experience – designed to connect data, devices, and teams. The current release includes tools for surgical video management, telepresence, and case planning, already rolled out in select hospitals.

We’re looking for a Mid-Level Backend Engineer to help build the core systems behind our AI platform. You’ll design scalable APIs, cloud microservices, and secure backend workflows that connect data and intelligent agents. It’s a hands-on role for someone who loves solving hard problems, shipping fast, and building clean, reliable systems in a startup environment.

Required Skills & Experience
• 3–6 years of backend development experience (Python, Node.js, Go, or similar).
• Solid understanding of microservice architecture, REST/GraphQL APIs, and distributed systems.
• Hands-on experience with AWS (Lambda, ECS/EKS, API Gateway, S3).
• Familiarity with containerization (Docker, Kubernetes) and CI/CD
pipelines.
• Understanding of data security and SOC 2–compliant development.
• Curiosity about AI/ML systems or willingness to learn how to build with them.

Preferred Skills & Experience
• Experience with AI workflow orchestration or LLM
integrations (OpenAI, LangChain, etc.).
• Familiarity with vector databases (Pinecone, Weaviate, Chroma).
• Knowledge of infrastructure as code (Terraform, CDK).
• Startup experience or comfort working in fast-paced, evolving
environments.

Key Responsibilities
• Build and maintain secure, scalable backend services and microservices on AWS
• Work closely with our AI and product teams to integrate LLMs, APIs, and data workflows.
• Contribute to system design, database schemas, and service orchestration.
• Implement and maintain SOC 2–compliant practices across code and infrastructure.
• Write high-quality, testable code with strong observability and monitoring.
• Optimize for performance, cost, and developer experience.

Softcery builds advanced AI systems for B2B SaaS companies. We partner with founders in the US and UK to design, build, and scale production-ready AI solutions that solve real business challenges. Our team focuses on complex AI engineering — systems that are technically robust, business-aligned, and built to scale.

We combine deep technical expertise with strong product thinking, helping companies move from AI ambition to real, production impact

We are looking for an AI Developer to join our team. If you are driven by AI, want to influence the product, and grow in a strong team — join us.

 

What You’ll Do:

• Integrate LLM into products — connect, configure, and optimize commercial LLM (OpenAI, Anthropic, Mistral, etc).
• Develop AI-oriented solutions — create chatbots, voice agents, and other AI products.
• Optimizing model performance — prompt engineering, reducing hallucinations, improving response productivity.
• Collaborating with the development team — integrating AI components into backend systems.
• Participation in technical calls with clients — presenting the current status of the project, gathering requirements, and clarifying expectations.
• Research and implementation of new AI solutions — analyzing new models, APIs, and frameworks to improve the company’s AI expertise.
  
   

What We’re Looking For:

• 2+ years of experience in AI/ML.
• Excellent knowledge of Python — most of our solutions are built on it.
• Experience with LLM (GPT, Claude, Gemini), prompt-engineering skills — you know how to integrate models into products and optimize prompts for specific tasks.
• Experience with SQL DBs — you have a good understanding of data structuring and can work with large volumes.
• Product mindset — you think not only technically, but also with the user’s needs in mind. Ready to look for the best solutions, not just “get the job done.”
• Fluency in Ukrainian and English (Upper-Intermediate+) — because communicating with customers is part of the job.
  
   

Nice to nave:

• Experience with fine-tuning models.
• Basic DevOps/MLOps skills.
• Knowledge of JS/TS.

What We Offer:

• Structured onboarding & dedicated support — you’ll get a clear onboarding plan, documented workflows, and a team that’s got your back.
• Flexible remote schedule — work from wherever and whenever you’re most productive.
• Learning budget — we cover books, courses, English lessons, and AI tools for your professional growth.
• Full accounting support — so you can focus on the work, not the paperwork.
• Time off — 20 paid vacation days, 12 sick days, 2 paid period leave days/month (for women), and your birthday off.
• IT Cluster membership — access to professional events and networking opportunities in the local tech community.

🔁 Hiring Process: Recruiter Interview → Tech Interview → Test Task → Final Interview.

If you care about who you work with, what you create, and how it affects the outcome, we will definitely be on the same page. We’re excited to meet you 👋