Jobs

N-iX is a global software development service company that helps businesses across the world develop successful software products. Founded in 2002, N-iX has come a long way, expanding its presence across Europe, the US, and Latin America. Today, we are a strong community of 2,000+ professionals and a reliable partner for global industry leaders and Fortune 500 companies. 

We are looking for an experienced Head of AI Consulting to head the AI Consulting direction within N-iX’s CTO Office. This is a strategic leadership role where you will shape our AI service offerings, drive technical pre-sales, lead high-impact projects, and build a world-class AI consulting team.

What will you do:

• Lead technical pre-sales as the primary consultant, scoping business and technical requirements for Gen AI (LLM, RAG, Agents), ML, CV, and related AI disciplines
• Become (or be ready to become) a world-class AI consultant for both clients and internal delivery teams
• Engage in short- and mid-term AI projects as a consultant/engineer to ensure successful execution and delivery
• Hire, manage, and mentor a team of AI consultants supporting pre-sales, project initiation, and delivery
• Collaborate with sales and marketing teams to refine and create new AI service offerings
• Partner with our alliances team to maintain and expand strategic partnerships (AWS, GCP, Azure, Nvidia, etc.)

• Report directly to VP of Data and AI Consulting, with dotted line supervision from the CTO of the company.

   

Requirements:

• 7+ years as an AI/ML/CV consultant with experience in pre-sales and delivery of both short- and long-term projects.
• 3+ years managing AI consultants or engineering teams.
• Experience in IT Service Business
• Strong leadership skills with excellent communication and client engagement abilities.

• Broad and deep understanding of AI technologies, trends, and methodologies.

   

What you will get:

• Lead one of N-iX’s most strategic practices within the CTO Office
• Collaborate with world-class clients on complex business and technology challenges (e.g., eBay, Bosch, Siemens, Credit Agricole, Office Depot)

• Build and lead a top-tier AI consulting team of passionate experts.

   

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings

• Other location-specific benefits

   

*not applicable for freelancers

About the Project

Join a high-performing UK-based product and cross-functional product team composed of top-tier engineers(PhD holders). We’re building an enterprise-grade data platform designed to integrate, process, and analyze vast amounts of disparate data in real-time.

This platform leverages cutting-edge technologies: Big Data, cloud-native architecture, AI-driven insights, and advanced database tooling to deliver deep operational visibility and power faster, smarter business decisions. We ensure scalability, traceability, and compliance (GDPR, HIPAA) through robust data lineage and governance features.

You’ll work mainly on AI services, having tight collaboration with backend developers to ensure seamless API integration. 

What You’ll Do

• Design and develop advanced AI components using LangChain, AutoGen, and other multi-agent orchestration frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using tools like Google AI Platform, Vertex AI and Pinecone.
• Engineer efficient prompts and fine-tune LLMs (e.g., GPT-4o, DeepSeek) for advanced data analytics capabilities
• Develop AI-related backend services using Python and FastAPI
• Deploy scalable solutions in Google Cloud Platform (GCP), working with services such as BigQuery, GKE, Cloud Storage, etc.

• Collaborate with backend and data engineering teams to integrate and expose AI functionality via well-structured APIs

   

Must-Have Skills

• 5+ years of experience in backend and AI system development
• Strong hands-on experience with LangChain, AutoGen, and multi-agent frameworks
• In-depth knowledge of LLMs, prompt engineering, NL2SQL, and RAG architectures
• Proficient in Python and FastAPI
• Proven experience with GCP services: Vertex AI, BigQuery, GKE, Cloud Storage
• Experience building production-grade RAG pipelines

• Excellent problem-solving and communication skills

   

Nice-to-Have

• Experience working with data engineering and DevOps tools
• Familiarity with data governance frameworks and compliance standards (GDPR, HIPAA)

• Exposure to real-time processing and scalable architecture patterns

   

Why Join Us

• Work with a world-class team on a cutting-edge AI and data platform
• High-impact role with room for innovation and growth
• Flexible schedule and remote-friendly setup
• Competitive compensation
• Collaborative, growth-oriented culture
• Engage in technically challenging, meaningful projects

Help us push AI further — and faster

LoopMe’s Data Science team builds production AI that powers real-time decisions for campaigns seen by hundreds of millions of people every day. We process billions of data points daily — and we don’t just re-apply old tricks. We design and deploy genuinely novel machine learning systems, from idea to prototype to production.

You’ll join a high-trust team that has a 5-star Glassdoor rating led by Leonard Newnham, where your work moves fast, ships to production, and makes measurable impact.

What you’ll do:

• Design, build, and run large-scale ML pipelines that process terabytes of data
• Apply a mix of supervised learning, custom algorithms, and statistical modelling to real-world problems
• Ship production-grade Python code that’s clear, documented, and tested
• Work in small, agile squads (3–4 people) with DS, ML, and engineering peers
• Partner with product and engineering to take models from idea → production → impact
• Work with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse and more

What you bring:

• Bachelor’s degree in Computer Science, Maths, Engineering, Physics or similar (MSc/PhD a plus)
• 4+ years’ commercial Python experience
• Track record building ML pipelines that handle large-scale data
• Excellent communication skills — comfortable working across time zones
• A curious, scientific mindset — you ask “why?” and prove the answer

Bonus if you have:

• Experience with adtech or real-time bidding
• Agile / Scrum experience
• Knowledge of high-availability infrastructure (ElasticSearch, Kafka, ClickHouse)
• Airflow expertise

About the Data Science Team:

We’re 17 ML engineers, data scientists, and data engineers, distributed across London, Poland, and Ukraine — acting as one team, not a satellite office.

What sets us apart:

• Led by an experienced Chief Data Scientist who codes, leads, and listens
• Inclusive, supportive culture where ideas are heard and people stay
• Strong values: open communication, continual innovation, fair treatment, and high standards
• Track record of publishing award-winning research in automated bidding

Don’t just take our word for it — check our Glassdoor reviews (search “Data Scientist”) for a real view of the culture.

About LoopMe:

LoopMe was founded to close the loop on brand advertising. Our platform combines AI, mobile data, and attribution to deliver measurable brand outcomes — from purchase intent to foot traffic. Founded in 2012, we now have offices in New York, London, Chicago, LA, Dnipro, Singapore, Beijing, Dubai and more.

What we offer:

• Competitive salary + bonus
• Billions of real-world data points to work with daily
• Flexible remote/hybrid options
• Learning budget and career growth support
• Friendly, transparent culture with strong leadership

Hiring process:

1. Intro with Talent Partner
2. 30-min technical interview with Chief Data Scientist
3. Panel with 2 team members (technical, culture & collaboration)
4. Offer – usually within 48 hours of final round

Are you ready to design and deploy AI systems that run at truly massive scale?

We are hiring an MLOps Engineer specializing in Large Language Model (LLM) infrastructure to design and maintain the robust platform on which our AI models are developed, deployed, and monitored. As an MLOps Engineer, you will build the backbone of our machine learning operations — from scalable training pipelines to reliable deployment systems — ensuring that our NLP models (including LLMs) can be trained on large datasets and served to end-users efficiently. This role sits at the intersection of software engineering, DevOps, and machine learning, and is crucial for accelerating our R&D in the Ukrainian LLM project. You’ll work closely with data scientists and software engineers to implement best-in-class infrastructure and workflows for the continuous delivery of AI innovations.

What you will do

• Design and implement modern, scalable ML infrastructure (cloud-native or on-premises) to support both experimentation and production deployment of NLP/LLM models. This includes setting up systems for distributed model training (leveraging GPUs or TPUs across multiple nodes) and high-throughput model serving (APIs, microservices).
• Develop end-to-end pipelines for model training, validation, and deployment. Automate the ML workflow from data ingestion and feature processing to model training and evaluation, using technologies like Docker and CI/CD pipelines to ensure reproducibility and reliability.
• Collaborate with Data Scientists and ML Engineers to design MLOps solutions that meet model performance and latency requirements. Architect deployment patterns (batch, real-time, streaming inference) are appropriate for various use-cases (e.g., a real-time chatbot vs. offline analysis).
• Implement and uphold best practices in MLOps, including automated testing of ML code, continuous integration/continuous deployment for model updates, and rigorous version control for code, data, and model artifacts. Ensure every model and dataset is properly versioned and reproducible.
• Set up monitoring and alerting for deployed models and data pipelines. Use tools to track model performance (latency, throughput) and accuracy drift in production. Implement logging and observability frameworks to quickly detect anomalies or degradations in model outputs.
• Manage and optimize our Kubernetes-based deployment environments. Containerize ML services and use orchestration (Kubernetes, Docker Swarm or similar) to scale model serving infrastructure. Handle cluster provisioning, health, and upgrades, possibly using Helm charts for managing LLM services.
• Maintain infrastructure-as-code (e.g., Terraform, Ansible) for provisioning cloud resources and ML infrastructure, enabling reproducible and auditable changes to the environment. Ensure our infrastructure is scalable, cost-effective, and secure.
• Perform code reviews and guide other engineers (both MLOps and ML developers) on building efficient and maintainable pipelines. Troubleshoot issues across the ML lifecycle, from data processing bottlenecks to model deployment failures, and continuously improve system robustness.

Qualifications and experience needed

Experience & Background:

• 4+ years of experience in DevOps, MLOps, or ML Infrastructure roles
• Strong foundation in software engineering and DevOps principles as they apply to machine learning
• A bachelor’s or Master’s in Computer Science, Engineering, or a related field is preferred

Cloud & Infrastructure:

• Extensive experience with cloud platforms (AWS, GCP, or Azure) and designing cloud-native applications for ML
• Comfortable using cloud services for compute (EC2, GCP Compute, Azure VMs), storage (S3, Cloud Storage), container registry, and serverless components where appropriate
• Experience managing infrastructure with Infrastructure-as-Code tools like Terraform or CloudFormation

Containerization & Orchestration:

• Proficiency in container technologies (Docker) and orchestration with Kubernetes
• Ability to deploy, scale, and manage complex applications on Kubernetes clusters; experience with tools like Helm for Kubernetes package management
• Knowledge of container security and networking basics in distributed systems

CI/CD & Automation:

• Strong experience implementing CI/CD pipelines for ML projects
• Familiar with tools like Jenkins, GitLab CI, or GitHub Actions for automating testing and deployment of ML code and models
• Experience with specialized ML CI/CD (e.g., TensorFlow Extended TFX, MLflow for model deployment) and GitOps workflows (Argo CD) is a plus

Programming & Scripting:

• Strong coding skills in Python, with experience in writing pipelines or automation scripts related to ML tasks
• Familiarity with shell scripting and one or more general-purpose languages (Go, Java, or C++) for infrastructure tooling
• Ability to debug and optimize code for performance (both in data pipelines and in model inference code)

ML Pipeline Knowledge:

• Solid understanding of the machine learning lifecycle and tools
• Experience building or maintaining ML pipelines, possibly using frameworks like Kubeflow, Airflow, or custom solutions
• Knowledge of model serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton, or custom Flask/FastAPI servers for ML)

Monitoring & Reliability:

• Experience setting up monitoring for applications and models (using Prometheus, Grafana, CloudWatch, or similar) and implementing alerting for anomalies
• Understanding of model performance metrics and how to track them in production (e.g., accuracy on a validation stream, response latency)
• Familiarity with concepts of A/B testing or canary deployments for model updates in production

Security & Compliance:

• Basic understanding of security best practices in ML deployments, including data encryption, access control, and dealing with sensitive data in compliance with regulations
• Experience implementing authentication/authorization for model endpoints and ensuring infrastructure complies with organizational security policies

Team Collaboration:

• Excellent collaboration skills to work with cross-functional teams
• Experience interacting with data scientists to translate model requirements into scalable infrastructure
• Strong documentation habits for outlining system designs, runbooks for operations, and lessons learned

A plus would be

LLM/AI Domain Experience:

• Previous experience deploying or fine-tuning large language models or other large-scale deep learning models in production
• Knowledge of specialized optimizations for LLMs (such as model parallelism, quantization techniques like 8-bit or 4-bit quantization, and use of libraries like DeepSpeed or Hugging Face Accelerate for efficient training) will be highly regarded

Distributed Computing:

• Experience with distributed computing frameworks such as Ray for scaling up model training across multiple nodes
• Familiarity with big data processing (Spark, Hadoop) and streaming data (Kafka, Flink) to support feeding data into ML systems in real time

Data Engineering Tools:

• Some experience with data pipeline and ETL
• Knowledge of tools like Apache Airflow, Kafka, or dbt, and how they integrate into ML pipelines
• Understanding of data warehousing concepts (Snowflake, BigQuery) and how processed data is used for model training

Versioning & Experiment Tracking:

• Experience with ML experiment tracking and model registry tools (e.g., MLflow, Weights & Biases, DVC)
• Ensuring that every model version and experiment is logged and reproducible for auditing and improvement cycles

Vector Databases & Retrieval:

• Familiarity with vector databases (Pinecone, Weaviate, FAISS) and retrieval systems used in conjunction with LLMs for augmented generation is a plus

High-Performance Computing:

• Exposure to HPC environments or on-prem GPU clusters for training large models
• Understanding of how to maximize GPU utilization, manage job scheduling (with tools like Slurm or Kubernetes operators for ML), and profile model performance to remove bottlenecks

Continuous Learning:

• Up-to-date with the latest developments in MLOps and LLMOps (Large Model Ops)
• Active interest in new tools or frameworks in the MLOps ecosystem (e.g., model optimization libraries, new orchestration tools) and a drive to evaluate and introduce them to improve our processes

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

About the Project

Join a high-performing UK-based product and cross-functional product team composed of top-tier engineers(PhD holders). We’re building an enterprise-grade data platform designed to integrate, process, and analyze vast amounts of diverse data in real-time.

We build next generation, Data & Cloud agnostic Process Intelligence solution that leverages process mining, knowledge graph, agentic eco-system & canvas to optimise enterprise process and proactivelly suggest and simulate improvements deploying agents into the customer system. 

What You’ll Do

• Design and develop advanced AI components using LangChain, Langraph,  AutoGen, and other multi-agent orchestration frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using tools like Google AI Platform, Vertex AI and Pinecone.
• Engineer efficient prompts and fine-tune LLMs (e.g., GPT-4o, DeepSeek) for advanced data analytics capabilities
• Develop AI-related backend services using Python and FastAPI
• Deploy scalable solutions in Google Cloud Platform (GCP), working with services such as BigQuery, GKE, Cloud Storage, etc.

• Collaborate with backend and data engineering teams to integrate and expose AI functionality via well-structured APIs

   

Must-Have Skills

• 5+ years of experience in backend and AI system development
• Strong hands-on experience with LangChain, AutoGen, and multi-agent frameworks
• In-depth knowledge of LLMs, prompt engineering, NL2SQL, and RAG architectures
• Proficient in Python and FastAPI
• Proven experience with GCP services: Vertex AI, BigQuery, GKE, Cloud Storage
• Experience building production-grade RAG pipelines

• Excellent problem-solving and communication skills

   

Nice-to-Have

• Experience working with data engineering and DevOps tools
• Familiarity with data governance frameworks and compliance standards (GDPR, HIPAA)

• Exposure to real-time processing and scalable architecture patterns

   

Why Join Us

• Work with a world-class team on a cutting-edge AI and data platform
• High-impact role with room for innovation and growth
• Flexible schedule and remote-friendly setup
• Competitive compensation
• Collaborative, growth-oriented culture
• Engage in technically challenging, meaningful projects
•  

About Busy RebelAt Busy Rebel, we aim to redefine the technology and innovation landscape, creating a distinctive ecosystem of exceptional talents while fostering ownership, inclusion, and diversity. We aim to catalyze societal and technological evolution by empowering tech entrepreneurs to challenge norms and spearhead change.

Busy Rebel aims to forge unparalleled partnerships, driving global impact through creative rebellion. We commit to being the trusted ally that amplifies visions with expert insight and inventive strategies, fostering a community of disruptive thinkers for technological empowerment and societal betterment. Every partnership and project is a step toward a more interconnected and enlightened world.

Be part of a company where every day is an opportunity to learn, challenge, and transcend the ordinary. Your journey with Busy Rebel is not just a career; it’s a pivotal chapter in the larger story of technological revolution and societal evolution. Join us, and let’s build the future together.
 

The Role:

We are looking for a Computer Vision Engineer to help us improve perception systems for UAVs.

You will work on computer vision pipelines, sensor integration, and visual-inertial approaches to enhance autonomous flight capabilities.

Must have:

• 2+ years of experience in robotics or autonomous systems
• Ability to read and write C++ code
• Python (prototyping, data analysis)
• OpenCV
• Understanding of IMU and camera systems (calibration, distortion)
• Machine Learning fundamentals (linear algebra, statistics, optimization)
• English: Intermediate

Nice to have:

• Experience in perception (localization, mapping, obstacle detection)
• SLAM or VIO frameworks (Vins-Mono, ORB-SLAM, etc.)
• Sensor fusion techniques (Kalman filters, multi-modal data processing)
• Real-time systems and optimization
• ROS/ROS2
• UAV or robotics testing experience
• GPU/NPU optimization (Jetson, Coral)

Responsibilities:

• Develop and improve computer vision pipelines for UAV perception
• Analyze system logs and performance metrics to identify bottlenecks
• Work with camera and IMU data
• Implement localization, tracking, and mapping algorithms
• Optimize algorithms for real-time performance on embedded hardware
• Participate in algorithm research and prototyping

What will you be doing:

• Design data science, statistical, machine learning and deep learning systems that influence millions of players
• Implement and optimize appropriate ML algorithms and tools for time series and tabular data
• Transform data science prototypes into full-scale products, while deploying and monitoring ML models
• Run live tests and experiments
• Train and retrain systems when necessary
• Create or extend existing ML libraries and frameworks

• Collaborate with other scientists, engineers, architects and analysts spread across several countries

   

Your Experience & Skills:

• MSc in Computer Science, or any related degree
• Solid working experience in Python and Java - high coding standards, clean code, well documented, and extensive unit testing- Must.
• Experience working with databases (SQL and no-SQL)
• Experience with Scala
• Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production
• Experience with machine learning frameworks (like Keras, Tensorflow, or PyTorch) and libraries (like scikit-learn) - Big Advantage. 
• Experience with Big Data tools, in particular batch and stream processing (Spark, Kafka, Hadoop, Hive, etc.) - Must 
• Good understanding of container & orchestration technologies (Docker, Kubernetes, etc.) - Must
• Experience working on high-scale, production-grade projects

• All-around team player who is a self-motivated, fast learner

   

Benefits:

• Annual company bonus
• Competitive salary & flexible working hours
• Daily breakfast, lunch, and office refreshments
• Private health insurance, dental coverage, and psychological counseling
• 20 paid vacation days and 5 sick days per year
• 6 long weekends and 1 day off for your birthday
• Gifts for special occasions (birthday, Easter, Christmas, Women’s and Men’s Day, weddings, childbirth, etc.)
• Technical library with the option to order books
• Access to our educational platform with courses, training programs, and certifications
• Career development through coaching and reviews
• Internal mobility & referral program
• Corporate celebrations, team-building events, and fun activities
• Personal care in the office (nails, eyebrows, and barber services)
• Modern offices (Kyiv, Vinnytsia, Dnipro) with organized shuttle buses to and from the office

Trueplay is a Loyalty Booster Suite that enables iGaming brands to build lasting customer relationships based on trust and mutual benefit. It features three programs that ensure player interactions with gambling platforms are exciting right from the start.

We offer solutions on three epic levels:

• Acquisition and engagement — CopyStake introduces users to an iGaming website, allowing them to bet alongside their favorite streamers.
• Retention — the Play to Earn and Hold to Earn loyalty programs keep player engagement high by guaranteeing rakeback and distributing a share of the platform’s revenue.
• Brand equity — the tokenization of loyalty points helps transform users’ affinity for a brand into a personal interest in its financial success. In Trueplay’s take on Web3 loyalty, players feel like casino stakeholders.

More than 20 iGaming brands from 18 markets are fostering player loyalty with Trueplay. 

Our internal team is currently looking for a skilled Senior ML Engineer.

It is important for us that you have:

• 5+ years of professional experience in software engineering/ML engineering
• Strong programming skills in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow)
• Solid experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes)
• Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, etc.)
• Knowledge of data engineering (ETL pipelines, streaming data, batch processing)
• Strong background in algorithms, data structures, and distributed computing
• Experience deploying and monitoring ML models at scale
• Excellent problem-solving and communication skills

You will be responsible for:

• Designing, implementing, and optimizing end-to-end ML pipelines (data preprocessing, model training, deployment, monitoring)
• Collaborating with data scientists to move ML models from research to production
• Ensuring scalability, reliability, and performance of ML services in production environments
• Developing tools for experiment tracking, model versioning, and reproducibility
• Working with big data platforms (Spark, Hadoop, Snowflake, Redshift, etc.)
• Implementing MLOps best practices (CI/CD for ML, monitoring, automated retraining)
• Conducting code reviews, mentoring junior engineers, and leading technical discussions

We offer:

• Remote work
• Two meeting hubs in Warsaw, Poland, and Kyiv, Ukraine
• Flexible working hours
• Compensation that includes coverage for 20 days to recharge and unwind
• Additional support covering 14 days for health-related matters when needed
• Support in professional growth during the initial months, with guidance from experienced team members
• Engaging corporate events and activities
• Competitive financial compensation

We are building a new development model where AI is not just a tool, but the core of the entire process. Our goal is to deliver products at high speed without compromising quality, using AI-first technologies such as GPT, Gemini, Claude, Replit AI, v0 by Vercel, Framer AI, Make, Bubble, and VibeOps.

As a Prompt Engineer, you will play a critical role in shaping how AI drives product creation. You will design, optimize, and manage prompts and workflows for large language models to generate high-quality prototypes, code, and automated processes. Your expertise will ensure that AI delivers precise, consistent, and production-ready results.

Key Responsibilities:

• Design, test, and optimize prompts for multiple use cases: UI generation, code creation, content writing, and automation flows.
• Build multi-step prompt chains and AI workflows (LangChain, LlamaIndex) for complex tasks.
• Configure and manage AI tools: GPT, Gemini, Claude, Cursor, Replit AI.
• Create templates and structured prompt frameworks for tools like v0, Framer AI, Base44, Relume.
• Collaborate with developers to integrate AI-generated outputs into production.
• Work with APIs and embed AI into development processes.
• Continuously analyze model outputs and improve accuracy and reliability.

Requirements:

• Hands-on experience with LLMs (OpenAI GPT, Anthropic Claude, Google Gemini).
• Strong understanding of AI-first development principles.
• Proven ability to craft effective prompts for coding, UI/UX, and content generation.
• Familiarity with AI tools: Replit AI, v0, Framer AI, Base44, Bubble, Make, n8n.
• Basic knowledge of web development (HTML, CSS, JS) or Python for integrations.
• English proficiency (Upper-Intermediate+).
• Bonus points for experience with LangChain, AI automation tools, CI/CD (Vercel, Netlify).

What We Offer:

• Work in an AI-first environment where innovation drives everything we do.
• Involvement in fast-paced projects with a KPI: full website development in 3 days.
• Flexible schedule and remote work options.
• Competitive salary + performance-based bonuses for achieving AI-first goals.
• Access to cutting-edge AI tools and the opportunity to experiment with next-gen technologies.
  
  Ready to shape the future of AI-driven development? Join us and be part of the team that builds products in days, not months.
  Apply now!

About

EdSpan is an innovative company in the EdTech space, building cutting-edge learning experiences for the next generation of students. Our collaboration with a US-based private school network helps us better understand user needs while expanding our B2C and B2B products to a broader audience. We are currently working on three major projects:

AI tutoring experience — an innovative project that brings real-time interaction with a 3D animated assistant powered by LLM technology. This virtual tutor helps students navigate challenges, provides guidance, and enhances the learning journey in a playful and engaging way.

Tutorpeers – a peer-to-peer tutoring platform with a young teachers marketplace, event booking features and Zoom-like online sessions with additional interactive learning tools.

Spark Incubator – LMS-like system designed to teach kids entrepreneurship.

We have well-defined processes, trying to automate routine things, conduct code reviews, use CI and CD pipelines to validate and ship our code. We use the Agile approach with daily stand-ups, bi-weekly sprints, and other Scrum artifacts. We keep the number of meetings to a minimum so that engineers can focus on writing high-quality code and delivering cool features.

Who you are

We’re hiring our first AI/ML Engineer to lead the development of our AI agents, including prompting, the RAG and evaluation pipelines, potential fine-tuning. So, you’ll play a key role in shaping the technical direction. We’re seeking someone with a strong understanding of machine learning and NLP fundamentals, capable of tackling complex challenges in agentic workflows and optimizing model performance across the stack.

Requirements

• At least 4 years of experience in the field of Machine Learning, working as a Data Engineer, Data Scientist, Machine Learning Engineer, or in a similar role.
• Bachelor’s degree in Computer Science, Mathematics, or equivalent practical experience;
• Proficiency in Python and common data science libraries (pandas, NumPy, scikit-learn);
• In-depth knowledge of machine learning principles, understanding of LLM architectures, prompt optimization, and fine-tuning strategies;
• Skilled in designing and optimizing RAG pipelines, including embedding generation, sparse and dense retrieval, and hybrid search techniques;
• Familiar with LLM evaluation metrics and tools (BLEU, RAGAS, DeepEval, and other);

• Upper-Intermediate level of English (B2) or above.

   

Highly desireable

• Proven experience building AI-driven workflows using frameworks such as LangGraph, AutoGen, or similar orchestration tools;

• Knowledge of AWS cloud and MLOps.

   

Responsibilities

• Design, implement, and optimize LLM prompts to ensure reliable outputs;
• Assist in developing and maintaining AI evaluation workflows, including designing evaluation guidelines and metrics;
• Help design and develop AI data pipelines: collection, storage, annotation, and model improvement;
• Leverage agent orchestration tools to improve and automate AI workflows;
• Collaborate with the product team to ensure AI capabilities power usable product features.

About PICHE

PICHE is Latvia’s leading business park development company with 20 years of experience and over 150 successfully implemented projects in Europe.

We specialize in the development, design, and building of business parks. PICHE is about an improved and organized work environment, so you can focus on what matters most at work.

Ready to lead real change with AI?
Join us and work side by side with one of the company’s top leaders to embed AI into the very core of how we operate — from accounting and procurement to workflow optimization and decision-making. This is a rare opportunity to not only deploy cutting-edge technologies but to shape how an entire organization thinks and works. If you’re passionate about real-world AI applications and want to see your work have a visible business impact — we want to talk to you)

We are currently looking for two specialists to expand our team.

Key Responsibilities:

• Design and implement company-wide strategies for integrating AI into core business operations.
• Partner with various departments to uncover opportunities where AI can streamline and enhance existing processes. 
• Apply machine learning models and smart algorithms customized for specific business use cases.
• Manage the seamless integration of AI tools into the current tech infrastructure. 
• Regularly assess the performance of AI systems to ensure they operate efficiently and reliably. 
• Serve as an internal advisor and mentor on AI topics, helping to build a culture of innovation and AI adoption.
• Stay ahead of industry advancements and embed the latest AI technologies into the company’s strategic plans. 
• Organize and lead internal workshops and training programs to build AI literacy and usage across teams.
   

Your Qualifications:

• Proven experience (1 year+) deploying and integrating AI solutions in real business environments.
• English B2.
• Hands-on experience with automation platforms like n8n, Make, Zapier, or equivalent tools.
• Strong communication skills, with the ability to work effectively across technical and non-technical teams. 

• Solid background in API integration within scalable system architectures.

   

Nice-to-Have Skills:

• Practical experience applying AI/ML in business workflows.
• Experience with automating business processes using AI or large language models (LLMs).
• Proficiency in designing and implementing API integrations and workflow automations. 
• Familiarity with cloud platforms such as AWS, Azure, or GCP for deploying AI solutions.
• Successful involvement in cross-departmental projects combining business and tech teams. 
• Working knowledge of modern LLMs like ChatGPT, Claude, or similar. 
• Background in digital transformation, product development, or innovation-focused roles. 
• Ability to code in Python or other AI-friendly programming languages.
   

We’re happy to provide you with:

• Salary from $1800+tax;
• Fully remote work opportunities;
• Breathtaking challenges, where everything is possible;
• Annual paid leave — 20 working days;
• Paid day off on your Birthday;
• Official national holidays are our days off;
• Сompensation for studies and sports;
• Corporate accountant support.

About the role:
We are looking for an AI Engineer who is passionate about building real-world AI products, not just conducting research or training models. This is a builder’s role for someone who can rapidly prototype, validate ideas, work with modern LLM frameworks, and create custom solutions when off-the-shelf tools are not enough.

You will work on complex multi-agent systems, drive architectural decisions, and ship production-grade features end-to-end.

Core Responsibilities:

• Designing and developing applications based on Large Language Models (LLMs).
• Building and implementing multi-agent systems.
• Using and extending modern AI frameworks (LangChain, CrewAI, etc.).
• Innovating and creating custom tools and patterns when needed.

• Working as a generalist with a strong understanding of the current AI landscape.

   

Requirements:

• Python is the primary programming language.
• Deep understanding of LLM application architecture and multi-agent systems.
• Hands-on experience with agentic frameworks (LangChain, CrewAI, etc.).
• Strong problem-solving and critical thinking skills.
• Familiarity with the stack: Postgres with PG vector, S3, AWS.

Nice to have:

• Experience with LLM fine-tuning (not required, as ML Engineers on the team handle this).

Ideal Candidate Profile:

• Autonomous and responsible, able to work with minimal supervision.
• Excellent communicator — able to clearly explain decisions and participate in technical discussions.
• Critical thinker who makes sound technical choices.
• Team player in a fully remote, international team (Europe + US EST).
• Has a builder mentality — enjoys writing code more than attending meetings.

What we offer

• Competitive salary + stock options.
• Fully remote work with a flexible schedule.
• Generous paid vacation and parental leave support.
• Budget for learning, conferences, and professional development.
• A strong international team with regular knowledge sharing.
• The ability to influence product architecture from day one.
• And most importantly, your work will have a real impact on millions of users worldwide.

Hiring Process

1. Intro call with recruiter (up to 30 min) — basic screening.
2. Live Technical Challenge (1 hour) — live coding with a proctor. Google allowed, no AI assistants. Straightforward for an experienced AI Engineer.
3. Interview with Head of AI (30 min) — focus on culture, work style, and expectations.
4. Final Team Interview (1–2 hours) — collaborative problem-solving session. Focus on reasoning, decision-making, and teamwork.

Quantum is a global technology partner delivering high-end software products that address real-world problems.

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organizations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn’t yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding the team and has brilliant opportunities for a Senior Data Science / LLM Engineer. The client is a technological research company that utilizes proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become “super-investors.”

Through our generative AI technology implemented into brokerage platforms and other financial institutions’ infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.

Must have skills:

• 4+ years of commercial experience as a Data Science Engineer
• Strong knowledge of linear algebra, calculus, statistics, and probability theory
• Knowledge and experience with algorithms and data structures
• 2+ years of experience with LLM and Natural Language Processing-related tasks
• Knowledge of modern DL architectures
• Experience with at least one of the Deep Learning frameworks (Tensorflow, PyTorch)
• Experience with SQL
• Strong knowledge of OOP
• At least an Upper-Intermediate level of English (spoken and written)

Nice to have skills:

• Experience with production ML/DL frameworks (OpenVino, TensorRT, etc.)
• Docker practical experience
• Experience with Cloud Computing Platforms (AWS, GCloud, Azure)
• Participation in Kaggle competitions

Your tasks will include:

• Full-cycle data science projects
• Data analysis and data preparation
• Development of NLP solution and AI-based chatbots
• Developing models and deploying them to production
• Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

Location: This role is based in the Netherlands, with a hybrid work option. Remote work is also available for candidates based in Poland or Portugal.

The role: As an AI Engineer, you will help shape how we use AI across the company. From improving data insights to creating new features powered by Large Language Models, your work will directly influence how teams collaborate and make decisions.

We are looking for someone who enjoys applying technology where it makes the most difference.

Responsibilities:

• Design, develop, and deploy machine learning models for practical use cases
• Integrate AI solutions into web, backend systems, and mobile platforms.
• Collaborate with cross-functional teams to define requirements and deliver AI features
• Build and maintain data pipelines for model training and inference
• Optimize models for accuracy, scalability, and performance
• Stay current with emerging AI frameworks, tools, and technologies
• Contribute to monitoring and troubleshooting AI systems in production
• Work extensively with prompt engineering:
  • Develop and optimize prompts for various use cases within AI-driven processes.
  • Design and improve conversation flows and agent workflows within AI systems.
• Work with LLMS

Requirements:

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field
• Proven experience in AI and machine learning development, 4 years and more
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.)
• Familiarity with cloud platforms (AWS,or GCP, or Azure)
• Experience with software engineering practices, including APIs, version control, and testing
• Experience designing robust AI agents and context-based workflows.
• Understanding of AI ethics and moderation for building safe AI solutions.
• Experience with Retrieval Augmented Generation
• Experience with Image Recognition Techniques
• Experience with prompt engineering required
• Good problem-solving skills and the ability to work in a collaborative environment
• Upper-intermediate English level or higher

Nice to have: Knowledge of MLOps practices and tools such as MLflow or Kubeflow

What we offer:

• Opportunity to work on real-world AI projects with measurable business impact
• Flexible working conditions
• Competitive salary depending on your experience with a comprehensive benefits package, which includes a monthly €50 stipend to cover work-from-home expenses, and an allocation of 25 vacation days.
• After one year, WeAreBrain offers access to a Team Reward Program for all employees.
• Innovative Exploration: Seize the chance to pioneer your department, venturing into uncharted territories, and experimenting with fresh ideas that push boundaries.
• Entrepreneurial: Immerse yourself in a true entrepreneurial environment where every team member is an owner.
• Office Perks: We organise lunch in the office and have monthly gatherings for drinks and bites, fostering our team spirit.
• Remote Work Flexibility: Our team has the freedom to work remotely, allowing you to achieve a healthy work-life balance that suits your preferences.
• Professional Growth: We value your growth. Take advantage of diverse opportunities and resources designed to nurture your professional development.
• A creative and dynamic work environment.

If you’re interested, please include your current location and salary expectations in the description when submitting your CV.

We are an IT services company based out of San Francisco, USA. ​​We build and acquihire expert engineering and data science teams to help our clients meet their business needs and solve their operational challenges

 

About the role

We are looking for an experienced Prompt Engineer with a strong background in QA and Product Management. This person will design, test and maintain prompts and prompt workflows for generative AI systems, focusing on answer quality, safety and product alignment. This role is non‑technical in the sense that heavy software development or ML engineering is not required; strong domain knowledge in testing, product requirements and evaluation is essential. You will take part in working with a lead conversion platform, powered by AI and integrations, helps local businesses convert leads faster, communicate easier, and make more sales. 

Key responsibilities

• Design, document and iterate prompt templates, system instructions and example-based scaffolding for LLM-driven features.
• Run structured test campaigns: create test cases, input datasets, acceptance criteria and test plans for prompt outputs.
• Send queries to AI models, evaluate responses for correctness, relevance, completeness, tone and safety; record findings and recommend prompt adjustments.
• Perform manual and semi-automated QA of model outputs across scenarios and edge cases; report bugs, hallucinations and biased or unsafe outputs.
• Define and maintain quality metrics, benchmarks and validation suites specific to prompt performance.
• Collaborate with Product Managers, UX designers, data owners and engineers to translate product requirements into prompt specifications and acceptance criteria.
• Prioritize issues and propose product-focused remediation (prompt rephrasing, context changes, guardrails, fallback behaviors).
• Maintain prompt documentation, versioning and change logs; create reproducible prompt examples and playbooks for internal teams.
• Monitor production prompt performance, escalate regressions and support rollout/testing of prompt updates.
• Contribute to ethical and safety reviews, help mitigate prompt injection and other prompt-specific risks.

Required qualifications

• Minimum 8 years total experience in the IT industry, with solid experience in QA and/or Product Management.
• Demonstrable experience evaluating and testing outputs of generative AI or rule-based systems (manual testing, test plans, acceptance criteria).
• Strong abilities in crafting clear, unambiguous written instructions and test cases.
• English: Upper-Intermediate (B2) or higher — comfortable reading technical docs and communicating with international teams.
• Analytical mindset, attention to detail, strong documentation skills and experience with defining QA metrics.
• Familiarity with common LLM usage patterns (prompt templates, few/zero-shot, RAG) and safety concerns (hallucination, bias, prompt injection).
• Comfortable using APIs or UI tools to interact with AI systems (no deep programming required).
• Experience working cross-functionally with product, design and engineering teams.

Preferred

• Prior hands-on experience as QA lead, Product Manager, or similar role in AI/ML product context.
• Experience with test automation frameworks or low-code tools for running prompt evaluation pipelines.
• Familiarity with tooling: OpenAI, Anthropic, Hugging Face, Retrieval systems, or prompt management platforms.
• Knowledge of privacy/regulatory requirements relevant to model outputs.