Jobs ML / AI

Atlas Technica’s mission is to shoulder IT management, user support, and cybersecurity for our clients, who are hedge funds and other investment firms. Founded in 2016, we have grown 100% year over year through our uncompromising focus on service.

We value ownership, execution, growth, intelligence, and camaraderie. We are looking for people who share our Core Values, thrive, and contribute to this environment while putting the customer first. At Atlas Technica, we offer a competitive salary, comprehensive benefits, and great perks to our global Team. We strive to maintain a professional yet friendly environment while promoting professional and career development for our Team Members. Join Atlas Technica now!

Design and deploy intelligent chatbots using Foundry Workflows, Microsoft Agent Framework, OpenAI. Build and operate multi-agent orchestration pipelines with Azure AI Foundry and Model Context Protocol (MCP). Integrate AI with enterprise systems via RESTful APIs, ensuring compliance with security and privacy standards. Stay current with LLM advancements, collaborate across teams, and mentor junior engineers.

Responsibilities:

AI Agent & Chatbot Development

• Design, build, and deploy intelligent conversational agents using Foundry Workflows, Microsoft Agent Framework, OpenAI.
• Develop prompt strategies and manage datasets to support context-aware, multi-turn dialogue and accurate responses.
• Conduct rapid prototyping to validate technical feasibility and demonstrate business value of AI-driven solutions.
• Design agentic loops with task decomposition, state passing between agents, and workflow enforcement for multi-step ticket resolution.

• Implement structured error responses and graceful degradation in agent tool calls, including timeout handling, retry logic, and fallback cascades.

   

Data & Model Engineering

• Build and maintain data ingestion and indexing pipelines for Azure AI Search and Cosmos DB.

• Evaluate and optimize AI system performance for accuracy, scalability, latency, and cost-efficiency.

   

System Integration & Architecture

• Architect and implement integration between AI and enterprise systems (e.g., ConnectWise PSA, Confluence, etc.) using RESTful APIs.
• Implement and maintain MCP servers (Model Context Protocol) for secure, typed tool integration between AI agents and enterprise APIs.
• Deploy containerized services to Azure using multi-stage builds and Azure Pipelines CI/CD.
• Security, Compliance & Governance
• Ensure AI systems comply with data privacy regulations (e.g., GDPR) and enterprise-grade security standards.

• Implement access controls, data encryption, and audit logging for sensitive AI workflows.

   

Research & Innovation

• Stay current with evolving LLM technologies, frameworks and methodologies.

• Evaluate emerging tools and techniques to continuously improve solution quality and delivery speed.

   

Collaboration & Leadership

• Work closely with cross-functional teams to interpret business requirements and recommend LLM-driven solutions.
• Contribute to technical and architectural decisions, ensuring alignment with strategic goals.

• Mentor junior engineers and support knowledge sharing across the team.

   

Operational Excellence

• Take ownership of incident resolution, and bug fixes.
• Create and maintain technical documentation for AI systems, models, and integration workflows.

Requirements:

• English level — B2 or higher
• 5+ years of experience in AI engineering and .NET software development (.NET 10, ASP.NET Core/WebAPI, C#) with frontend experience in React 19 / Next.js 15 / TypeScript, with a focus on Azure-based solutions.
• Experience building intelligent chatbots and autonomous agents (Agentic AI) that perform real actions, plan, reason, and act with minimal human input; familiar with multi-agent orchestration and agent memory.
• Strong expertise in embeddings, search, and prompt engineering.
• Strong understanding of large language models (LLMs), their limitations, and modern capabilities (e.g., GPT, Claude, Gemini).
• Hands-on experience with Azure AI services (Azure AI Foundry, Azure OpenAI, Azure AI Search) and hands-on experience with MCP or similar protocols for secure, scalable integration between AI agents and enterprise systems.
• Familiarity with multi-agent orchestration patterns: coordinator-subagent workflows, maker-checker validation, signal-based confidence scoring, and context preservation across multi-turn interactions.
• Experience designing prompts with explicit evaluation criteria, few-shot techniques, structured output via JSON schemas, and validation/retry loops for reliable LLM responses.
• Awareness of AI-specific security concerns: PII handling, data boundary enforcement, prompt injection prevention, and compliance considerations (e.g., GDPR).

• Ability to write clean, maintainable, and testable code following SOLID principles and Clean Architecture patterns.

   

Desirable Qualities:

• Understanding of AI solution architecture patterns: LLM gateway/service layer, retrieval layer, orchestration/agent layer, and evaluation/observability layer.
• Experience testing AI-enabled components using deterministic seams (mocked LLM clients, retrievers, tools), scenario-based tests, and regression/evaluation datasets for non-deterministic outputs.
• Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
• Familiarity with AI/ML versioning practices: prompt version control with semantic tagging, evaluation baseline tracking, dataset versioning, experiment reproducibility.
• Familiarity with deploying, monitoring, and maintaining ML models in production environments.
• Experience with Azure Cosmos DB, Azure Container Apps, Docker containerization
• Familiarity with CI/CD pipelines and DevOps practices.
• AI-102
• Experience with Application Insights telemetry, distributed tracing.
• Prior experience integrating AI agents with enterprise platforms like ConnectWise PSA, Confluence, SPO, etc.

Atlas Technica is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

We are looking for a Middle ML & AI Engineer to join us as part of our team.

About the role

PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high-volume of data for the PitchBook Platform and surface insights for the capital markets. A strong motivation to succeed is critical and everyone has the opportunity to shape the long-term direction of our team.

About the project

PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more.

Team

Engineering Manager, 6 ML & AI Engineers.

Work Environment

The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert, You will

• Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges.
• Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis.
• Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights.
• Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing.
• Collaborate & Communicate: Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively.
• Tech Stack & Focus Areas: Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems. Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources.

We’re looking for you if you have

• Bachelor’s/master’s degree in computer science, Machine Learning, Statistics, or related fields.
• 3+ years of experience in a similar role in a production environment.
• Experience in transformer-based language models
• Proficient in deep learning frameworks (i.e, TensorFlow and PyTorch)
• Demonstrated experience with natural language processing.
• Demonstrated experience with Python or other object-oriented programming frameworks.
• Demonstrated experience in using SQL for data extraction.
• Strong communication and data presentation skills.
• Strong problem-solving ability.
• Ability to communicate complex analysis in a clear, precise, and actionable manner.
• Experience working closely with software development team(s) is a plus.
• Experience building scalable systems in production is a plus.
• Knowledge of financial services, investment, banking, VC, and/or PE is desired but not required.

What’s in it for You

Reveal great tech solutions

Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.

Experience an agile and flexible working environment

Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.

Embrace the opportunity for personal and professional growth

Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more.

Be among like-minded people

Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.

Interview steps

1. Pre-Screening with the recruiter
2. Tech Interview + Live Coding (up to 1,5 hours)
3. System Design interview (up to 45 min)
4. Final interview with Engineering Manager (45 min)

Seeking a founding AI engineer to develop real-time speech to text systems for military and emergency services, focusing on Python, in Warsaw.

The company is a European defence tech startup building modern software for military and emergency services, with a focus on high-stakes, hostile environments. Backed by top VCs and strategic partners, the company is assembling a world-class founding team to deliver real-world impact

This Founding AI Engineer role exists to drive the development of bespoke, real-time speech-to-text systems for initial customers, working closely with the founders in a fast-moving, ambiguous environment.

You’ll work closely with the founders to evolve our early stack and help service our first customers (French, German, Ukrainian, and Polish military units, as well as emergency services).

Requirements:

• Experience with implementing Voice AI systems in resource constrained environments
• Strong execution skills
• Desire to build from zero

• Ability to thrive in ambiguous, fast-moving environments

   

Conditions:

•  Compensation will depend on experience; expected range €70–110K + equity
• On-site in Warsaw, Poland; relocation and visa sponsorship are available for strong candidates. 
• Candidates must be able and willing to work from the office in Warsaw.

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

We are looking for a Senior ML & AI Engineer to join us as part of our team.

About the role

PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical, and everyone has the opportunity to shape the long-term direction of our team.

About the project

PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials, and many more.

Team

Engineering Manager, 6 ML & AI Engineers

Work Environment

The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert, You will

• Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges.
• Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis.
• Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights.
• Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing.
• Mentor & Lead: Act as a mentor for junior team members and stay updated on trends in Agentic AI, transformer models, and generative systems.
• Collaborate & Communicate: Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively.
• Tech Stack & Focus Areas:
• Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems.
• Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources.

We’re looking for you if you have:

• Educational Background: You hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field.
• Experience: You bring 4+ years of production experience in the ML field, with a track record in developing transformer-based models and deploying them in scalable systems.

• Technical Expertise:

  - Proficient in Python and machine and deep learning frameworks like TensorFlow, PyTorch, ScikitLearn, Spacy, or others.

  - Experienced in natural language processing and modern LLM-based techniques.

  - Experience with full ML lifecycle, data preprocessing, training, evaluation stage, and monitoring techniques.

  - Skilled with SQL and data extraction methods.

• Innovative Thinker: You thrive on solving complex problems and are always exploring new trends in Generative AI.
• Collaborator & Communicator: You’re an excellent communicator able to collaborate and professionally express your thoughts to team members, other engineering teams, and stakeholders.
• Domain Knowledge: Exposure to financial services, investment banking, venture capital, or private equity is nice to have.

What’s in it for You

Reveal great tech solutions

Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients.

Experience an agile and flexible working environment

Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work.

Embrace the opportunity for personal and professional growth

Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learning through the corporate library, public speaking support, and more.

Be among like-minded people

Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program.

Interview steps

• Pre-Screening with the recruiter
• Technical interview (up to 90 min)
• System Design interview (up to 45 min)
• Behavioral Round with Product Manager (45 min)
• Final interview with Engineering Manager (60 min).

We’re looking for an Applied AI Engineer who combines strong ML fundamentals with the discipline of improving production AI systems through metrics, evaluation, and iteration.

This role is hands-on, product-focused, and collaborative with the AI platform lead.

The role in a nutshell

You’ll work on improving production AI systems through evaluation, experimentation, and system design.

A large part of the role involves:

• diagnosing failures in agent workflows
• designing evaluation metrics and KPIs
• improving system prompts and agent behavior
• running structured experiments and measuring impact

You won’t be working in isolation on research projects — you’ll be improving systems that real users depend on.

Rough responsibility breakdown:

• AI evaluation and KPI design — ~30%
• Prompt and agent system design — ~30%
• ML systems (recommendation, optimization, etc.) — ~30%
• Engineering integration — ~10%

What you’ll work on:AI evaluation and system quality

• Design evaluation strategies for LLM and agent workflows
• Create metrics and KPIs for AI system performance
• Build and maintain evaluation datasets
• Debug production AI failures systematically
• Compare system behavior against baselines

This is a core responsibility of the role.

Multi-agent AI systems

• Improve agent orchestration and workflows
• Diagnose failures across agent pipelines
• Refine system prompts and agent interactions
• Improve reliability, latency, and response quality

ML and AI systems

You’ll contribute to areas such as:

• Recommendation systems (ranking and personalization)
• Itinerary optimization and constraint-based planning
• LLM-based reasoning systems
• Optional: computer vision pipelines

Depth in one of these areas is more important than superficial experience in all of them.

Engineering collaboration

We use:

• Golang (primary production language)
• Python when necessary for ML workflows
• Postgres, Redis, and internal services

You don’t need to be a Go expert on day one, but you should be comfortable reading and modifying production code.

Backend engineers handle infrastructure-heavy service development — your focus is AI system behavior and correctness.

What we’re looking forMust-haves

Strong AI/ML fundamentals You understand the theory behind what you build and can choose appropriate methods for a problem.

Examples:

• evaluation metrics (precision/recall/F1/etc.)
• ranking and recommendation concepts
• embeddings and similarity
• experimentation methodology

Not required:

• academic publications
• advanced theoretical math
• large-scale model training experience

Evaluation-driven mindset You:

• think in metrics and baselines
• design experiments instead of guessing
• measure system improvements quantitatively
• debug failures methodically

This is the most important signal for the role.

Experience with LLM systems You’ve worked with:

• prompt design
• agent workflows
• evaluation of LLM outputs
• production LLM integrations

Ability to ship production systems You can:

• turn ideas into working systems
• iterate based on results
• balance exploration with delivery

Programming ability You’re comfortable writing production code in at least one language (Python, Go, or similar) and learning others when needed.

Strong signals (nice to have)

• Experience improving an AI system after deployment
• Recommendation systems or ranking experience
• Optimization or constraint-based systems
• Computer vision experience
• Experience building evaluation frameworks
• Golang experience
• Startup or small-team engineering experience

This role may not be a fit if

• You are looking for a research focused role without production deployment
• You rely heavily on frameworks without understanding fundamentals
• You’re uncomfortable working with partially-defined problems
• You prefer narrow specialization over product ownership

We are looking for a Machine Learning Engineer to design and implement intelligent systems that power personalized digital experiences across connected devices and mobile applications.

This role is ideal for someone who thrives at the intersection of ML models, data pipelines, and product integration. You will collaborate closely with backend engineers, data scientists, and product managers to bring ML-driven features into production and continuously optimize them based on real-world usage.

Responsibilities:

• Design, train, and deploy machine learning models for use cases such as personalization, recommendations, and visual analysis;
• Build and maintain scalable, production-grade data pipelines (batch and real-time);
• Collaborate with product and engineering teams to translate product ideas into ML-powered features;
• Implement model observability, monitoring, and retraining workflows;
• Optimize inference performance and model serving in resource-constrained environments (e.g., edge or mobile);
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;

• Work with backend teams to expose model outputs via APIs and integrate them into customer-facing experiences.

   

Requirements:

• 3+ years of experience in applied machine learning or data science;
• Strong knowledge of:
  • Supervised learning, recommendation systems, or computer vision;
  • Python and ML libraries such as TensorFlow, PyTorch, scikit-learn;
  • Building, deploying, and maintaining ML models in production.
• Familiarity with:
  • MLOps tools (e.g., MLflow, TFX, Airflow, Vertex AI);
  • Data pipelines and messaging systems (e.g., Kafka, BigQuery, dbt);
  • Model serving frameworks (e.g., FastAPI, TensorFlow Serving, TorchServe, ONNX);
• Comfortable collaborating with product, engineering, and analytics teams;
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Bonus: Experience with edge AI, mobile ML, or video/image processing pipelines.

We Offer:

• Remote work and flexible working hours.
• Legal support.
• Paid sick leaves.
• Paid vacations.
• Medical insurance. 
• Free English classes.

About Us

Our client is MilTech startup building an on-premises platform for automated annotation of UAV video and training computer vision models for autonomous flight.

We have a strategic partnership with one of the largest Ukrainian UAV manufacturers and access to what is likely the largest privately owned UAV video dataset in the world.

The company is at a very early stage — the funding is secured, the technical vision exists, and the data is available. Our focus now is building the core engineering team to turn this platform into reality.

The Role

We are looking for aComputer Vision / Machine Learning Engineer.

We are looking for  CV/ML Engineer to join as one of the first engineers on the team. You will work closely with the technical lead to build the ML pipeline from the ground up — implementing core components across data processing, model training, and deployment.

This is an early-stage startup, so the tech stack and processes are still being shaped. You will have real input into the tools and approaches we adopt, and your work will directly define how the platform operates. We are looking for someone who is hands-on, curious, and comfortable building things that don’t exist yet.
 

What You Will Work OnData Pipeline & Preprocessing

• Build video preprocessing pipelines: clip segmentation, frame extraction, scene detection, quality filtering
• Implement embedding extraction and data curation workflows for selecting diverse training subsets from a massive video corpus
• Prepare and export datasets in standard formats for training and annotation
   

Model Training & Experimentation

• Train and evaluate computer vision models for object detection, classification, tracking, and segmentation
• Run experiments, track results, and iterate on model architectures and hyperparameters
• Implement data augmentation strategies for robustness across weather, lighting, and occlusion conditions
• Contribute to distributed multi-GPU training pipelines
   

Active Learning & Annotation Support

• Implement auto-labeling pipelines with confidence-based routing
• Build tooling around the annotation platform (pre-annotation, format conversion, quality
• Maintain automated quality checks for label consistency
   

Edge Deployment

• Export and optimize models for inference on NVIDIA Jetson (ONNX, TensorRT, FP16/INT8quantization)
• Run accuracy and latency benchmarks on edge devices
• Help maintain the model delivery pipeline from training to deployment
   

Requirements Must Have

• 3+ years of hands-on experience in computer vision and deep learning
• Solid PyTorch skills — comfortable writing training loops, custom datasets, and model code
• Experience with at least one detection or segmentation framework (YOLO family, Detectron2, MMDetection, or similar)
• Understanding of model evaluation metrics (mAP, IoU, precision/recall)
• Familiarity with experiment tracking (MLflow, W&B, or similar)
• Python as primary language; clean, well-structured code
• Comfortable working in Linux and containerized environments (Docker)
   

Nice to Have

• Model optimization experience (ONNX export, TensorRT, quantization)
• NVIDIA Jetson or other edge/mobile deployment
• Multi-object tracking (ByteTrack, DeepSORT, or similar)
• Experience with video processing pipelines (FFmpeg, OpenCV, decord)
• Data curation or annotation tools (FiftyOne, CVAT, Label Studio)
• Distributed training (DDP, Ray Train)
• UAV / drone / robotics or MilTech domain experience
   

What We Offer

• Join an early-stage team where your contributions shape the product from day one
• Work across the full ML pipeline — not just one narrow piece
• The largest privately owned UAV video dataset in the world — petabyte-scale, impossible toreplicate
• Dedicated on-prem GPU resources — no cloud queues or budget negotiations for compute
• Open-source-first approach with no vendor lock-in
• Growfast in a small team with direct mentorship from the technical lead

As a Senior ML Engineer, you will work on retention and churn prediction models built on large-scale behavioral datasets.
You will focus on feature engineering, model development, and building reliable training and batch inference pipelines that transform player activity data into production-ready predictive systems.
This role combines strong analytical thinking with practical ML engineering skills and close collaboration with the ML Lead.

Responsibilities

• Build and improve churn and retention prediction models using player behavioral data
• Design time-based features (rolling windows, aggregates, decay metrics)
• Train, validate, and iteratively improve gradient boosting models
• Develop reproducible training and batch scoring pipelines
• Analyze model performance and refine feature sets

• Support deployment of models into production scoring services

   

Requirements

• 4+ years of experience in ML Engineering / MLOps with production systems.
• Strong Python for ML and data processing (NumPy, pandas, scikit-learn)
• Experience with gradient boosting models (CatBoost, XGBoost, LightGBM)
• Experience building predictive models on tabular event data (churn, retention, risk)
• Strong understanding of time-based feature engineering and leakage-safe modeling
• Experience building ML training and batch inference pipelines
  Strong analytical and statistical thinking

Would Be a Plus

• Experience with behavioral feature engineering (rolling windows, aggregates)
• Experience with clustering or user segmentation
• Experience deploying ML services (FastAPI, Docker)
• Experience with ML lifecycle tools (MLflow or similar)
• Experience with workflow orchestration tools (Airflow, Prefect, Dagster)
• Experience with AWS or similar cloud environments
• Experience with deep learning frameworks (PyTorch / TensorFlow)

Tech Stack

• Python, NumPy, pandas, scikit-learn
• CatBoost / XGBoost
• SQL
• FastAPI, Docker
• MLflow (or similar)
• AWS or similar cloud environment

What We Offer

• Full ownership of a greenfield ML platform.
• Direct impact on revenue-driving retention systems.
• High level of autonomy in technical decisions.
• Competitive compensation.
• Flexible working format.
• Opportunity to shape the ML engineering foundation of the product.

Candidates should have hands-on experience building end-to-end Azure data and machine learning platforms, including most of the following:

Designing and operating ETL / ELT pipelines in Azure 
Experience with Azure Data Factory for orchestration 
Experience with Azure Databricks for large-scale data processing 
Experience using Azure Data Lake Storage as the core data platform 
Building data pipelines that feed machine learning model training 
Experience with Azure Machine Learning or equivalent ML training platforms 
Implementing feature engineering pipelines and dataset versioning 
Experience operationalizing models and integrating predictions into production systems 
Working with large datasets and high-throughput pipelines

AI / ML Pipeline Experience 
The candidate should have experience building systems where data pipelines directly support AI/ML workflows, including: 
Preparing training datasets from raw operational data 
Building repeatable model training pipelines 
Managing feature engineering workflows 
Supporting model retraining and lifecycle management 
Designing systems where trained models are consumed by applications or services 
Ensuring pipelines support scaling training workloads efficiently

On behalf of our client, we are looking for a Senior MLOps Engineer (GCP / Kubeflow)

 Requirements:

- Strong experience in MLOps / ML infrastructure

- Hands-on experience with GCP (Vertex AI, GCS, BigQuery, Cloud Run)

- Experience with Kubeflow, Docker, and Kubernetes

- Strong Python skills

- Experience building ML training & evaluation pipelines

- Experience with CI/CD and Infrastructure as Code (Pulumi or similar)

- Experience with model monitoring & observability tools (Grafana, TensorBoard, etc.)

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

We present an engaging opportunity to explore and work with various technologies beyond ChatGPT prompts. You’ll have the flexibility to transition between teams, enabling you to contribute to diverse projects, including complex LLM training pipelines, 3D generative AI, diffusion models, and multimodal edge ML.

Our team comprises experts in the foundational elements of next-generation AI systems, encompassing multimodal inference, generative reasoning, and robust training pipelines. We also maintain an in-house GPU cluster, providing resources for interacting, training, and experimenting with larger models for both professional projects and personal exploration.

Joining our team — means joining a knowledgeable group of researchers and engineers in an environment eager to stay at the forefront of AI innovation, a critical endeavor in today’s rapidly advancing AI landscape.

Requirements:
• Strong Python Experience (3 year +)
• Experience with building Generative AI projects
• Specialized experience with LLMs, LangChain, LangGraph, LangFuse, RAG, and related technologies
• Experience in building REST APIs, knowledge of Docker, relational & vector DBs
• At least upper intermediate written/spoken English
• Be able to visit the office at least 3 times a week

Would be a plus:
• Experience with building Voice-to-Voice AI Systems using LiveKit or similar frameworks
• Knowledge of existing yet fresh AI tools, AI marketplaces, etc.
• Knowledge of various machine learning methodologies, including classic machine learning, recommendation engines, natural language processing, computer vision, and beyond
• C/C++ knowledge
• Experience in edge ML

Key Responsibilities:
• Tackle tough problems and find creative ways to solve them
• Maintain and optimize the solution for maximum speed and flexibility
• Guide, tune, and train LLMs
• Write clean and reusable code
• Improve your skills and stay up-to-date with emerging technologies

What We Offer:
• Startup culture, a strong goal-oriented team, and a research mindset
• Opportunity to leverage your engineering skills for fellow engineers and shape the future of AI
• Working with the newest technical equipment (Latest MacBook Pro)
• 20 working days of annual vacation leave
• English courses, Educational Events & Conferences
• Medical insurance

Hello! We’re looking for a motivated and tech-savvy Junior AI Specialist to join our team at Kevych Solutions. If you have some experience building AI-driven systems and want to level up by working on complex, real-world business challenges — from autonomous agents to sophisticated n8n workflows — this role is for you.

Key responsibilities:

1. Building and testing AI agents and conversational systems for lead research, client outreach, and pipeline management;
2. Designing and refining LLM interactions to improve conversation quality and task performance;
3. Automating business processes using n8n — integrating databases, scraping tools, and outreach platforms;
4. Supporting data collection and processing to enable targeted outbound campaigns;
5. Collaborating with team members to improve AI-driven workflows and propose better strategies.

Requirements:

1. Up to 1 year of hands-on experience in AI implementation or workflow automation;
2. Experience working with LLM APIs (OpenAI, Claude, Gemini) and/or agent frameworks;
3. Experience with Python, JavaScript/TypeScript;
4. Familiarity with vector databases (FAISS, Pinecone, pgvector);
5. Basic understanding of AI cost optimization, latency, prompt engineering, and RAG pipelines;
6. Practical understanding of n8n — or strong motivation to learn it quickly (experience building flows, connecting APIs, etc.);
7. Strong problem-solving skills and the ability to independently conduct online research and experimentation;
8. Ability to work with semi-structured data (JSONs, CSVs);
9. Knowledge of REST APIs and backend integrations;
10. Experience with Git;
11. Upper-intermediate level of English (written and verbal);
12. A self-starter with a learning mindset — not afraid to test, iterate, and improve;

Good to know:

1. Understanding ML fundamentals;
2. Experience with Docker and cloud environments (AWS/GCP);
3. Experience working with multi-agent orchestrations.

Hiring Process:

1. HR interview (up to 45 minutes);
2. Test task;
3. Technical interview (up to 45 minutes);
4. Final interview (1 hour).

Sprinterra is a technology and consulting company delivering custom software solutions and digital transformation initiatives for clients in the US and Europe. We combine strong engineering practices, Agile delivery, and business-oriented thinking. A key focus for Sprinterra is the adoption of AI-driven solutions - both internally and in client projects - to significantly increase efficiency, quality, and scalability.

Role Overview
We are looking for a senior executive technology leader who will own and drive Sprinterra's overall Technology and AI vision at the company level. This role carries full responsibility for defining, implementing, and scaling our AI-first transformation strategy across internal operations, delivery models, and client solutions.

The primary objective is to reposition Sprinterra as an AI-enabled organization by systematically transitioning from traditional manual processes to AI Agents, intelligent automation, and augmented engineering workflows.

This role operates at the executive level in close partnership with the Management Board, contributing to company-wide strategic decisions, investment priorities, capability development, and long-term technology positioning.

The Technology & AI Strategy Lead combines strategic leadership with architectural oversight and hands-on technical credibility. In addition to setting direction, this leader ensures execution, guiding teams, shaping complex solution architectures, supporting pre-sales initiatives, mentoring senior engineers, and acting as the ultimate technical authority within the organization.

Why join Sprinterra?
This is a rare opportunity to define and implement an AI-first transformation from the ground up. You will shape how a growing international technology company evolves its delivery model, internal operations, and client solutions through AI Agents and intelligent automation.

As Technology & AI Strategy Lead, you will operate as a key executive partner to the Management Board, directly influencing company strategy, investment priorities, and long-term market positioning.

Your decisions will shape:

• How we work
• What we build
• How we compete
• How we scale

Key Responsibilities
AI & Technology Strategy

• Define, own, and continuously evolve Sprinterra's overall Technology and AI strategy at the company level
• Identify and prioritize strategic opportunities to transition from traditional delivery models to AI Agents, LLM-driven workflows, and intelligent automation
• Establish and govern a long-term AI transformation roadmap fully aligned with business objectives, growth targets, and market positioning
• Advise and report to the Management Board on technology vision, investment priorities, progress, risks, and measurable outcomes
• Lead company-wide adoption of AI tools, frameworks, and engineering standards
• Drive organizational evolution toward AI-augmented delivery models and next-generation engineering practices
• Define and enforce standards, governance models, and best practices for responsible, secure, and scalable AI implementation
• Ensure all AI initiatives meet enterprise-grade expectations in quality, security, compliance, and ethical responsibility

Hands-on Engineering & Architecture

• Provide executive-level technical oversight and intervene hands-on in strategically critical or high-complexity projects when required
• Define architectural principles and review system and AI architectures across the organization
• Ensure solutions are scalable, secure, maintainable, and aligned with long-term technology strategy
• Act as the ultimate technical authority and escalation point for complex architectural or engineering challenges

Pre-Sales & Technical Sales

• Lead and shape technical pre-sales strategy in collaboration with Sales and Delivery leadership
• Define high-level system architectures and AI-driven solution approaches for strategic client proposals
• Serve as a trusted executive-level technical advisor in client meetings, workshops, and negotiations
• Translate complex business challenges into differentiated, AI-enabled technology solutions that strengthen Sprinterra's market position

Required Skills & Experience

• 10+ years of progressive experience in software engineering, system architecture, and technology leadership
• Proven track record of defining and executing company-level technology and AI strategies
• Strong practical experience with AI/ML, LLMs, AI Agents, and intelligent automation in production environments
• Demonstrated ability to lead large-scale technology transformations, not just individual projects
• Hands-on technical background with the ability to dive deep when strategically necessary
• Experience aligning technology initiatives with business strategy, growth objectives, and market positioning
• Executive-level communication skills, with the ability to influence board members, senior stakeholders, and clients
• Experience leading technical pre-sales, shaping solution strategy, and representing technology at the executive client level
• Strategic leader with full ownership mindset and accountability for outcomes
• Capable of balancing long-term vision with disciplined execution
• Confident decision-maker comfortable operating with ambiguity and high impact
• Influential communicator able to align leadership, engineering, and business teams
• Drives change rather than maintaining status quo
• Trusted advisor to executive leadership and key clients

Вимоги до володіння мовами

Англійська

B2 – Вище середнього

Українська

B2 – Вище середнього

Про компанію Sprinterra

Sprinterra is an outsourcing company in the Ukrainian IT market, founded in 2002 and rebranded in 2016. For over 19 years the company has been helping various organizations to achieve their goals. Sprinterra serves Financial, Healthcare, Real estate, Retail and other verticals. Our clients are US and European companies looking for high quality software development services. We provide a full cycle of software development: our team creates system components, integrates existing platforms and develops new turnkey solutions. Sprinterra meets the specific needs of each client using a wide range of technologies, including application and Web development, DevOps, data management, low-code platforms, Cloud, Mobile, AI. Why Sprinterra? - continuous development, interesting projects; - opportunity for professional growth and career development;  - the ability to work remotely; - flexible schedule.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

At PwC, we work together to help clients make informed decisions, operate efficiently, and shape the future. Join our consulting team specializing in Generative AI as an AI Engineer. Our Technology Advisory team drives innovative projects every day, guiding companies through major technological changes. Current projects include applying large language models and generative AI in finance and energy sectors, as well as improving internal efficiency and accelerating workflows with AI tools.

What You’ll Do:

• Design and develop AI solutions using Large Language Models (LLMs), including advanced techniques like Retrieval-Augmented Generation (RAG) and multi-agent systems.
• Turn ideas into working prototypes and lead Proof of Concept (PoC) projects from planning to delivery.
• Apply the latest AI research to real-world challenges in industries like finance and energy.
• Collaborate with diverse teams to identify new use cases and deliver impactful solutions.

What We’re Looking For:

• 4+ years in software development, with at least 2 year in AI systems (RAG or agent-based).
• Strong Python knowledge, familiarity with databases (especially vector databases), and understanding of AI ecosystems.
• Basic knowledge and use of multi-agent systems, guardrail solutions, and orchestration frameworks (e.g., LangGraph).
• Proactive, solution-oriented, and able to work independently as well as in a team.
• Upper-intermediate English proficiency.

What We Offer:

• Work with leading experts on innovative projects that matter.
• Rapid career growth and continuous learning opportunities.
• Flexible schedule, hybrid work options, and a supportive environment.
• Competitive salary, annual bonus, and benefits including private healthcare, wellness programs, and home office allowance.
• A vibrant community with team-building events and a modern office in a prime location.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

Strong Backend Engineer + basic LLM experience

Position Summary 

The Generative AI Solutions Engineer is responsible for building AI-powered backend features and automation components using modern LLM APIs. The role requires strong backend engineering fundamentals in any mainstream programming language (Python, Node.js, PHP or similar), the ability to analyze requirement documents, convert them into technical structure, and deliver rapid proof-of-concept implementations. 

The work focuses on creating practical solutions, integrating external APIs, generating structured outputs, and developing reusable components that accelerate software development and reduce manual effort. 

This is not a research or academic AI position — it is a hands-on engineering role focused on real-world business and product needs. 

Key Responsibilities 

• Build backend services using Python or Node.js. 
• Integrate with LLM APIs (OpenAI, Claude, Mistral and so on). 
• Process requirement documents and extract structured information. 
• Generate module-level breakdowns and engineering estimations. 
• Create API or backend prototypes for high-level requirements. 
• Build helper scripts/tools that reduce repetitive engineering work. 

Required Technical Skills 

• Strong backend engineering skills (Python / Node.js / PHP or similar) 
• Experience building and consuming REST APIs 
• SQL basics and database design understanding 
• Ability to produce backend prototypes rapidly 
• Experience working with JSON and external APIs 
• Familiarity with LLM APIs (OpenAI, Claude, Mistral or similar) 

Nice-to-Have 

• LangChain or LlamaIndex experience. 
• Some prompt engineering experience. 
• Docker basics. 
• Internal developer tooling experience. 
• Ability to analyze incomplete requirements. 

Fit Profile 

Best fit for someone who: 

• likes real engineering more than research, 
• enjoys prototyping solutions, 
• understands system behavior and data flows, 
• can operate with limited documentation, 
• can deliver results within short timeframes. 

What this role is NOT 

• Not academic AI research 
• Not ML model training 
• Not data science 
• Not RPA automation 
• Not prompt-engineering-only 

Why the role is attractive 

• build working AI-first solutions 
• solve real customer challenges 
• high autonomy, low bureaucracy 
• meaningful systems, not demos 
• highly visible impact 

This is NOT a research job. You will build real AI-powered software that solves real business problems. 

We offer:

• Salary according to qualifications and experience;

• Official employment.

• 21 working days of paid vacation.

• 14 days paid sick leaves.

• Work on challenging web application projects which we deliver to our clients from all over the world (North America, Europe, Australia, Asia).