Jobs ML / AI

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 Senior AI Engineer to join our European client developing software for the digital advertising market. As a Senior AI Engineer, you will develop a programmatic trading platform that optimizes advertising experience for advertisers, publishers, and mobile users.

This is you

• 6+ years of experience in AI/ML engineering;
• Strong knowledge of OpenRTB and bidding flows;
• Deep understanding of CPV, CPE, and CPC campaign types;
• Proficiency in PySpark and pandas for data processing;
• Experience with FastAPI for API development;
• Hands-on with Docker for containerization;
• Expertise in LightGBM and ONNX for model training and deployment;

• English – Upper-intermediate level or higher.

   

Nice-to-have skills:

• Familiarity with Metaflow for ML workflows.

   

This is your role

• Develop specialized models for CPV, CPE, and CPC campaign types;
• Integrate AI solutions with an existing Demand-Side Platform (DSP);
• Optimize bidding flows using OpenRTB protocols;
• Lead the AI/ML team in model development and deployment;
• Design and implement scalable AI architectures for real-time bidding systems;
• Collaborate with cross-functional teams to align ML strategies with business goals in programmatic advertising.

Description
About ProfiSea Labs 
ProfiSea Labs is an innovative AI-powered multi-cloud management platform designed to help CloudOps engineers and IT managers optimize cloud usage, reduce costs, and automate workflows through intelligent, next-generation technologies. 
We’re building a new AI division focused on agentic GenAI systems — autonomous agents capable of reasoning, learning, and interacting with users and systems. We’re looking for curious, ambitious minds to help us design, train, and scale these agents. 

Requirements
 

• English C1+ (strong writing and reading skills). 
• Python knowledge — basic to intermediate. 
• Excellent literacy and attention to detail. 
• Experience with LLMs (e.g. GPT, Gemini, Claude, Copilot). 
• Understanding of Agentic AI design or prior experience building agents is a plus. 
• Analytical mindset and creativity in solving interaction problems. 
• Strong interest in AI technologies and willingness to learn continuously. 
• Students or recent graduates are welcome to apply — the main requirement is your curiosity and drive to grow. 

Responsibilities

 

• Develop, optimize, and test AI prompts and workflows in English. 
• Create dialogues, flows, and interaction scenarios for AI agents. 
• Tune the agent’s behavior across various contexts. 
• Work with test flows, analyze failures, and improve model responses. 
• Collaborate with product managers, designers, and developers to integrate AI into real products. 
• Experiment with LLMs (Large Language Models) and contribute to fine-tuning and configuration processes. 

Test Task 
A short technical and creative task will be required to assess Python proficiency, prompt design ability, and reasoning skills. 

Working conditions
 

• Opportunity to take part in building an innovative AI product. 
• Ongoing learning and mentorship from experienced AI engineers. 
• Flexible schedule and fully remote work. 
• Competitive compensation. 
• Friendly and professional work culture. 
• Freedom to influence product development and bring your own ideas to life. 

 
At ProfiSea Labs, we don’t just use AI — we teach it to think. Join us if you’re ready to do the same.

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 the Role
We are seeking a skilled AI & Machine Learning Engineer with deep experience in computer vision, model development, and MLOps pipelines. 

The ideal candidate will work closely with robotics and software teams to design and deploy intelligent systems for automated blade
surface inspection, defect detection, and autonomous perception.

Key Responsibilities
• Design algorithms for feature extraction, defect classification, and visual analytics
• Develop and train deep learning models (CNNs, transformers) using PyTorch or
TensorFlow
• Create automated data ingestion, labeling, and preprocessing pipelines
• Integrate MLOps tools (Azure ML, MLflow, Kubeflow) for retraining, validation, and
deployment
• Optimize models for edge deployment (Jetson, Raspberry Pi) and ROS2 integration
• Ensure proper data management and maintain AI development documentation.

Requirements

• Proven experience (min. 8+ years) in computer vision, deep learning, and AI model
deployment
• Strong understanding of neural network architectures, data pipelines, and MLOps tools
• Familiarity with edge computing and ROS2 integration is a plus
• Fluent in English (asynchronous communication with global teams)

• An articulate English (due to asynchronous communication with a global, English-
speaking team)

• A home office with fast and stable internet connection (15Mb/s), modern laptop/PC,
noise-cancelling headset and access to a quiet workspace

About Bitmedia Labs
Bitmedia Labs - an international product IT company, has been in the industry since 2014, effectively functioning on a worldwide scale with a crew of 130+ ambitious and highly skilled professionals, creating successful projects in domains such as online advertising systems for the crypto space, blockchain games, and NFT products.

We are currently looking for an experienced engineer to join our R&D project, contributing to cutting-edge development and innovation within the company.

Required Qualifications:
 

• 3+ years of software engineering experience, with 2+ years working with LLMs and generative AI
• Strong Python development skills in a production environment (clean code, typing, testing, Git)
• Experience with both proprietary (OpenAI, Anthropic, Gemini) and open-source LLMs (LLaMA, Mistral)
• Working knowledge of orchestration frameworks (LangChain, LlamaIndex)
• Hands-on experience building RAG pipelines and working with vector databases (Pinecone, Weaviate, Qdrant, pgvector, or similar)
• Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT) and understanding of when to fine-tune vs. use RAG or prompt engineering
• Practical prompt engineering skills: structured outputs, function/tool calling
• Experience building backend services and APIs (FastAPI or Flask)
• Solid SQL skills and experience with databases (PostgreSQL, MongoDB, Redis, or Elasticsearch)
• Ability to debug LLM-specific issues (hallucinations, retrieval quality, cost/latency), work independently, and communicate technical decisions clearly.
   

Preferred Qualifications:
 

• Experience with agentic workflows and multi-step orchestration (LangGraph, CrewAI)
• Cloud deployment experience (AWS, GCP, or Azure), Docker, CI/CD
• Open-source model serving and inference optimization (vLLM, TGI, quantization, caching)
• Advanced retrieval techniques: hybrid search, reranking, query rewriting
• Familiarity with LLM evaluation and observability tools (RAGAS, DeepEval, LangSmith, Arize Phoenix)
• Knowledge of AI safety practices: prompt-injection prevention, PII handling, guardrails.

Hiring process: 
 

• Intro call with a Recruiter - Technical Interview with the Hiring team - Collection of Recommendations - Offer.
   

We offer:

• Flexible work environment - you can work remotely from anywhere;
• The 8-hour working day with a flexible schedule;
• Competitive salary based on your experience;
• Regular performance review and annual salary review;
• Paid sick leaves, vacation, and holidays;
• Professional development tools (reimbursement of educational courses or workshops, conferences around the world);
• Ambitious team with transparent communication and a friendly atmosphere, no micromanagement;
• Apple equipment;
• Memorable gifts for holidays.

We are looking for an AI Engineer (Research & Development). As an AI Engineer, you will join the R&D team working on AI products and help scale the AI offering through marketing activity.

Skills and experience you can bring to this role!

Qualifications & experience:

• You are particularly interested in emerging AI tech, LLMs, and generative AI. You follow the news, new developments, and academic research. You are excited about its potential impact on product development in the upcoming years;
• You are interested in going beyond the technical side. You could work as a consultant, demonstrate an understanding of business and product aspects, and generate product ideas;
• You understand and can explain how business value could be generated out of the use of AI technologies;
• You have built ML/AI powered solutions and used available services & tools and/or built bespoke ML models/solutions;
• You've investigated the practical application of generative AI/LLMs through pet projects and PoCs, exploring ready-to-go products, and you can demonstrate or discuss the output;
• You have experience in LLMs/SLMs assessment, selection, and fine-tuning for the specific use case;
• You enjoy writing code, preferably in Python and have 3+ years of experience in commercial development;
• You know what prompt engineering, vector databases, embeddings, multi-stage reasoning, RAG, and MLOps are, and you have had a practical (could be non-commercial) experience with some of the listed things;
• You enjoy communication and can talk to both technical and non-technical stakeholders.

Nice to have: 

• You have previous experience in data engineering;
• You are active in the growing AI community, attend webinars, events, and meetups, or are interested in becoming active;
• You have some front-end experience building simple UIs to demonstrate solutions end-to-end or are open to gaining such;
• You are interested in developing a personal brand through participation in content creation in collaboration with marketing & AI Lab.

What impact you’ll make

• Participate in research and development activities by working on Star's internal AI products;
• Create proof of concepts for our clients and prospects, focusing on applying AI technologies;
• Monitor and research changes in the AI developer ecosystem and approaches and apply them in practice to develop Star's AI capabilities;
• Participate in client calls during late sales cycle stages, present technical expertise, and help build solutions; 
• Act as a subject matter expert on AI to assist with Star's marketing and branding efforts.

Join Innoneers – Shaping the Future of Software Engineering!
 

At Innoneers, we don’t just build software; we engineer innovation. We are a dynamic software development company dedicated to transforming complex business challenges into seamless digital experiences. Specializing in Web, Mobile, and Cloud solutions, we pride ourselves on our technical agility and "Engineering Excellence" mindset.
 

As we scale our operations, we are looking for a passionate Embedded ML Engineer to join our core team. If you thrive in an environment where clean code meets cutting-edge technology (Node.js, React, AWS, Python) and want to make a tangible impact on global projects in E-commerce, Fintech, and Logistics, Innoneers is the place for you.
 

WE WILL TRUST YOU WITH:

• Lead the design and implementation of state-of-the-art machine learning algorithms

  tailored for both real-world hardware and software applications;

• Build and optimize embedded ML models using PyTorch and NumPy, bringing them

  to life in embedded systems with C and Python;

• Analyze, benchmark, and fine-tune embedded ML pipelines to achieve latency,

  memory efficiency, and power optimization;

• Pioneer explainable AI techniques that provide actionable insights into model

  behavior and drive trustworthy solutions for our customers and end-users;

• Expand our ML toolkit by researching and integrating the latest methodologies,

  staying at the forefront of AI innovation;

• Establish scalable, reproducible workflows that set a standard for excellence in

  embedded ML development;

• Partner with a multidisciplinary team of hardware engineers, data scientists, and

  software developers to deliver integrated software and hardware application use

  cases;

• Provide critical algorithm insights to hardware development teams to facilitate

  seamless integration and performance optimization;

• Support the integration of ML models with hardware AI accelerators and

  neuromorphic processors;

• Collaborate with internal teams and clients to identify and design requirements for

  complex customer use cases;

• Translate customer needs into technical specifications and actionable project plans;
• Present findings and insights to stakeholders to inform decision-making and strategy;

• Mentor junior engineers and interns, fostering a culture of continuous learning and

  technical excellence within the team;

• Contribute to the creation of intellectual property, including patents and proprietary

  know-how.

   

YOUR EXPERIENCE INCLUDES:

• A BSc or MSc in a subject related to ML/Data Science/Statistics or relevant industry

  experience;

• Solid understanding of architecture specifications, and the ability to design and

  develop industry-standard embedded software and methodologies;

• 5+ years of hands-on experience in the development and deployment of AI solutions;
• Previous experience in Embedded or TinyML AI application development;

• Proficiency in C/C++ for logical programming for embedded software development

  and Python for ML model development;

• Strong experience with TensorFlow/PyTorch and Scikit-learn;
• Familiarity with hardware AI accelerator architectures and neuromorphic processors;
• Experience working with time series data/sensor data/real-time data processing;

• Proficiency in using version control systems.

   

WHAT YOU NEED TO SUCCEED:

• Strong analytical and problem-solving abilities with great attention to detail;

• Excellent communication skills for effective collaboration with cross-functional team

  and stakeholders;

• A proactive and self-motivated attitude toward learning and innovation.

   

WE OFFER YOU:

• A dynamic working environment around a fearless engineering culture;
• Ambitious teams with the freedom to innovate;

• A Flexible working environment (work from home policy, flexible working hours,

  advantageous holidays scheme ..);

• An inclusive company culture that embraces communication, diversity, and support

  around holistic and personal development.

Middle Computer Vision & ML Engineer — Founding Team

About Us

We are a newly funded MilTech startup building an on-premises platform for automated annotation of petabytes of UAV video and training computer vision models for autonomous flight. We have a strategic partnership with the largest Ukrainian UAV manufacturer and access to what is the largest privately owned UAV video dataset in the world. We are at the very beginning — the technical plan exists, the funding is secured, the data is real — and now we need the right people to turn it into reality.

The Role

We are looking for a Middle 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 On

Data 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 validation)
- Maintain automated quality checks for label consistency

Edge Deployment
- Export and optimize models for inference on NVIDIA Jetson (ONNX, TensorRT, FP16/INT8 quantization)
- Run accuracy and latency benchmarks on edge devices
- Help maintain the model delivery pipeline from training to deployment

What We Are Looking For

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

Proposed Tech Stack

This is our starting point — the stack is still being finalized, and you will have input into the choices we make.

- Training: PyTorch, distributed training (DDP/FSDP) 
- Data processing: Ray Data or equivalent scalable framework 
- Data curation: FiftyOne, embedding-based selection 
- Annotation: CVAT with pre-annotation and active learning 
- Experiment tracking: MLflow 
- Edge: ONNX → TensorRT → NVIDIA Jetson 
- Infrastructure: Kubernetes, on-prem GPU cluster 
- Storage: S3-compatible object storage (Ceph) 

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 to replicate
- Dedicated on-prem GPU resources — no cloud queues or budget negotiations for compute
- Open-source-first approach with no vendor lock-in
- Grow fast in a small team with direct mentorship from the technical lead
- Competitive salary
- Stock option
 

About the Role

We are building a large-scale conversational AI platform focused on personalized human–AI interaction. The product operates at significant real-world scale, serving tens of millions of users and processing over 80 million tokens per day. The platform works in a complex domain that requires advanced alignment, moderation, and low-latency inference.

We are looking for a Tech Lead to take ownership of the LLM direction and lead a small team of AI engineers. This is a hands-on role combining system design, model development, and production engineering. The product operates in an uncensored / NSFW environment, which requires careful, context-aware moderation rather than simplistic safety filters.
 

What You Will Do

• Lead and build the LLM systems powering the core conversational experience. You will architect and evolve the core chat loop, including context windows, memory and RAG pipelines, and inference performance.
• Own the full model lifecycle, including prompt design, supervised fine-tuning, and preference optimization. You will make decisions on when to fine-tune models, when to redesign retrieval pipelines, and how to manage data quality at scale.
• Design and implement moderation and alignment systems suitable for an explicit environment. This includes building custom classifiers and moving beyond binary safe/unsafe decisions toward nuanced, context-aware moderation.
• Work closely with DevOps and backend teams to deploy, monitor, and continuously improve production systems used by millions of users globally.
   

Requirements

• You have 8+ years of engineering experience and a strong track record of shipping ML or LLM-based systems to production at scale.
• You are highly proficient in Python and PyTorch and familiar with modern LLM tooling and infrastructure.
• You are comfortable working with NSFW content and understand the technical and ethical challenges of moderating explicit conversational systems.
• You have strong intuition for LLM behavior, including how prompting, sampling, and alignment techniques affect model outputs.
• You prioritize practical, shippable solutions and take ownership of system reliability, performance, and user impact.
   

Team & Environment

You will lead a small LLM team and collaborate closely with DevOps and web/backend engineers. The environment emphasizes autonomy, direct communication, and a strong bias toward execution and measurable impact.

We are seeking an experienced Mid/Mid+ Data Scientist with expertise in Large Language Models (LLMs) such as GPT, Claude, and related technologies. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and deep learning models. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across our product lines.

Responsibilities:

‌

• Design, develop and optimize Large Language Models for various NLP tasks such as text generation, summarization, translation, and question-answering
• Conduct research and experiments to push the boundaries of LLM capabilities and performance
• Collaborate with cross-functional teams (engineering, product, research) to integrate LLMs into product offerings
• Develop tools, pipelines and infrastructure to streamline LLM training, deployment and monitoring
• Analyze and interpret model outputs, investigate errors/anomalies, and implement strategies to improve accuracy
• Stay current with the latest advancements in LLMs, NLP and machine learning research

• Communicate complex technical concepts to both technical and non-technical stakeholders

   

Requirements:

‌

• MS or PhD degree in Computer Science, Data Science, AI, or a related quantitative field
• 2-3+ years of hands-on experience developing and working with deep learning models, especially in NLP/LLMs
• Expert knowledge of Python, PyTorch, TensorFlow, and common deep learning libraries
• Strong understanding of language models, attention mechanisms, transformers, sequence-to-sequence modeling
• Experience training and fine-tuning large language models
• Experience with classical ML models - XGBoost, LightGBM
• Proficiency in model deployment, optimization, scaling and serving
• Excellent problem-solving, analytical and quantitative abilities
• Strong communication skills to present technical information clearly
• Ability to work collaboratively in a team environment

• Fluency in Ukrainian and English

   

Preferred:

• Research experience in LLMs, NLP, machine learning
• Experience working with multi-modal data (text, image, audio)
• Knowledge of cloud platforms like AWS, GCP for model training
• Understanding of MLOps and production ML workflows
• Background in information retrieval, knowledge graphs, reasoning

🟠 Details: we are looking for an ML/AI Engineer (ASR) to fine-tune and optimize an Automatic Speech Recognition system for Swiss German. In this role, you will work hands-on with PyTorch and Hugging Face to adapt pretrained ASR models, build reproducible training pipelines, and improve recognition accuracy through data quality refinement and controlled experimentation (WER/CER).

🟠 About the project: our client is advancing a speech recognition solution with a strong focus on dialect adaptation and real-world audio robustness. The current phase centers on dataset preparation and validation, model fine-tuning (e.g., Whisper), decoding and language-model optimization, and data-centric quality improvements to achieve production-grade transcription accuracy across diverse speakers and conditions.

🟠 Qualifications:

• Solid experience in automatic speech recognition (ASR) systems.
• Practical experience with model fine-tuning and evaluation, including metrics such as WER and CER.
• Strong hands-on proficiency with PyTorch and the Hugging Face ecosystem.
• Good understanding of decoding strategies (e.g., beam search) and integration of language models.
• Familiarity with data-centric AI approaches and dataset quality improvement practices.
• English language proficiency at B2 level (upper-intermediate) and above.

🟠 Would be a plus:

• Experience adapting models for multilingual or dialectal speech.

🟠 Responsibilities:

• Prepare and validate speech datasets, including audio—text alignment, normalization, and dataset splitting.
• Build and maintain reproducible training pipelines using PyTorch and Hugging Face tools.
• Fine-tune pretrained ASR models (e.g., Whisper) for target data and use cases.
• Apply established ASR training techniques such as SpecAugment, curriculum learning, and decoding optimization.
• Improve pseudo-label filtering workflows and overall training data quality.
• Design and run controlled experiments to evaluate models and reduce WER.
• Deliver reproducible training configurations, model checkpoints, and clear technical documentation.

🟠 Interview steps:

• Screening with Recruiter (about 30 minutes).
• Interview with Project Manager (about 30 minutes).
• Call with the client (about 1 hour).

🟠 By joining us, you will get:

• Accounting coverage and lawyer support.
• Paid Vacations.
• Paid 4 paid public holidays (New Year, Independence Day, Day of the Defender of Ukraine, and Christmas).
• Flexible working hours and the possibility to work remotely.
• Best-class working equipment (laptop and accessories).
• Good conditions for skills development: the possibility of upgrading your English for business needs due to working time and 50% coverage for studying English; the offer of internal workshops; and wellbeing sessions as one-to-one meetings.

🟠 Our office in Lviv:

• FuturaHUB, located in Lviv (Kulparkivska 200a).
• An inspiring, modern workplace with a great atmosphere and development culture.
• “Happy Hours” parties.
• Yoga and sports training in FuturaHUB.
• Chill-out area: gaming zone with PlayStations, table tennis & table soccer.
• Beer, coffee, tea, cookies, etc.
• Conference rooms.

🟠 Some of our Values:

• No overtime and pressure.
• Regular rest and burnout control.
• Clean relationships within the company and with the client.
• Responsibility for the own development, ideas, and interests communication, as well as for the problems that stand in the way of this development.
• Openness to the new, readiness for changes.

We are building the next generation of AI Agentic Marketing Solutions specifically for the Game Development industry. We don’t just build simple chatbots; we build autonomous agents that plan, execute, and optimize User Acquisition (UA) and marketing campaigns for gaming studios.

We already have our technical leadership in place. Now, we are looking for a highly autonomous Senior Engineer who loves "getting their hands dirty" with complex agentic logic and scaling our AI platform.

The Role: Builder First

This position is for those who are passionate about coding and want to remain in a technical, individual contributor role. We need a "crafter" who enjoys diving into agent architectures, optimizing RAG pipelines, and writing high-performance code without the distraction of people management or "ivory tower" meetings.

Our Stack: Python (FastAPI, AsyncIO), LangChain / LangGraph, Redis, PostgreSQL, AWS.

Key Responsibilities

• Develop AI Agents: Design and implement complex, stateful workflows using LangGraph.
• Hands-on Engineering: Serve as a primary contributor to the core Python codebase. We expect daily commits and rapid iteration.
• Production-Grade AI: Work on agent reliability, mitigate hallucinations, manage agent memory systems, and build robust evaluation loops.
• Integrations: Connect AI agents with gaming metrics, store APIs (App Store/Google Play), and ad platform dashboards.
• Performance Tuning: Optimize LLM usage for latency and cost-efficiency.

Requirements

• Python Mastery: 5+ years of professional experience in Python. Deep expertise in AsyncIO, Pydantic, and FastAPI.
• AI/LLM Expertise: Proven experience with LangChain or LangGraph (essential). You understand the transition from simple prompts to complex, autonomous agentic reasoning.
• Solid Engineering Foundation: Strong knowledge of architectural patterns, event-driven systems (NATS/Kafka), and Vector Databases (Pinecone, Weaviate, etc.).
• Startup DNA: You prefer "shipping today" over "perfecting tomorrow." You thrive in a fast-paced environment where speed is a core feature.
• GameDev Interest: A genuine interest in the gaming industry and its KPIs (LTV, ROAS, Retention).

What We Offer

• Focus on Code: Minimal bureaucracy. Your time is spent solving hard technical problems, not in management meetings.
• High Impact: Your code directly defines the "intelligence" of our marketing agents.
• Elite Team: Work alongside a Technical Lead and other senior experts who value excellence and relentless improvement.
• High Reward for High Performance: Competitive salary + Advanced Bonus System (We reward those who build the business with us).
• A professional team that has your back. We work hard, but we support each other 100%.
• Medical Insurance in Ukraine and Multisport program in Poland.
• Offices in Ukraine (Kyiv, Kharkiv) and Poland (Wroclaw) or Remote.
• All necessary equipment and workstation space.
• Legal & Accounting services.
• English classes and Education reimbursement.
• Incredible corporate parties and other activities (when we aren't saving the world).

Our client is a company that is one of the prominent providers of unique online slot games based in Spain. We are looking for AI Platform Engineer to join our team building internal tools for automation and analytics in slot game development.

Required skills:

Must-have:

• 3+ years of experience in developing internal tools/automation.
• Python 3.10+, FastAPI, async/await, typing.
• SQL/PostgreSQL (schemas, indexes, window functions, materialized views).
• SaaS API integrations (Atlassian preferred), webhooks, error handling.
• Docker (multi-stage builds, docker-compose), basic logging and monitoring.
• Hands-on experience with AI assistants (Copilot, Cursor, Claude Code) and a culture of code verification.

Responsibilities:

• Build integrations with Jira, Confluence, Slack: REST API, webhooks, OAuth2; normalize and load data into PostgreSQL.
• Create dashboards (onboarding, lead time/throughput, workload, overdue tasks, AI automation impact) in Metabase/Superset or lightweight React panels.
• Develop small backend services: FastAPI endpoints, schedulers, alerts; handle rate limits, retries, and idempotency.
• Support the ML team: prepare datasets for RAG/vector search, collect telemetry on AI feature usage.
• Use AI assistants (Copilot, Cursor, Claude Code) for prototyping, refactoring, and test generation — always with proper verification.

• Write short documentation (README, ADR) together with tech/UX writers.

   

Сompanу offer:

• Work on impactful internal tools that directly improve team efficiency.
• Opportunity to actively use AI assistants and be at the forefront of AI-driven development.
• Modern tech stack.
• Flexible schedule and remote-first culture.

This role is a hybrid Data Ops + ML Engineer position responsible for both data ingestion foundations and AI/ML capability. The platform analyses real customer conversations alongside CRM and campaign data to surface actionable insights for revenue teams. Having successfully delivered a working MVP, the next phase is focused on scaling, improving observability, and laying the foundation for multi-client onboarding. This is a "ground-up" ownership role, setting the standards for data and ML scale-out during a high-growth phase.

About the Product

• The platform is designed to identify customer patterns faster for marketing and commercial teams. It sits at the intersection of B2B, SaaS, LLMs, and sales enablement.
• Al-native platform: Analyses customer conversations and related
  sales/marketing data.
• Modern Stack: Built on a cloud-native stack using Google Vertex AI and serverless workloads.
• Status: A functional MVP is complete and entering scaling and
  enhancement.

Responsibilites

Data Ops

• Extend and automate ingestion connectors including email, transcripts, and conversational tools.
• Maintain standardised metadata and traceability from source to insight.
• Define and evolve data models that support RBAC, analytics, and AI
  retrieval.
• Own data quality validation, schema alignment, and error monitoring.

ML/LLM Engineering

• Improve prompt design, error-handling, and structured output quality.
• Optimise token cost, latency, grounding strategy, and hallucination
  safeguards.
• Introduce evaluation metrics for insight quality and utilisation.
• Partner with engineering for scalable model deployment and lifecycle management.

Must-Have Experience & Skills
Technical Requirements

• Experience: 4+ years in data engineering / ML engineering hybrid teams preferred.
• Languages: Python required.
  Cloud & Infra: Google Cloud Platform, especially Vertex AI and Cloud
  Functions.
• Data Platform: PostgreSQL experience and data modeling capability.
  ETL/Ingestion: Airbyte, Cloud Composer, or similar ingestion orchestration.
• MLOps: API-driven LLM integration (OpenAI, Anthropic, Vertex).
  Soft Skills & Behaviours.
• Ownership mindset: Accountable for outcomes, not just tasks.
• Bias for action: Pragmatism over perfection.
• User empathy: Focuses on AI that feels useful, not just functional.

Success Criteria
First 3-6 Months:

• Ingestion Foundation: Robust, automated ingestion supporting multiple formats and sources.
• Data Quality: Tagging, validation, and metadata enabling meaningful
  downstream AI.
• Insight Consistency: Prompts and model config deliver repeatable, trusted insight patterns.
• Observability: Clear dashboards, alerting, and data lineage controls.

Engagement Details

• Number of Roles: 1
• Target Start Date: February 2026
• Engagement Type: Potential Temp to Permanent hire after 6 months, but primarily looking for perm options
• Location: Fully remote (Core collaboration on UK hours)
• Working Hours: 8h per day
• Core overlap required: 10:00–16:00 London (GMT/BST)

Assessment Process
1. CV & GitHub/Portfolio review.
2. Technical screening (Data + ML scenarios).
3. Live ingestion / prompt engineering exercise.
4. Founder + leadership interview for culture and ownership fit.

What We Offer:

• Full remote with flexible business hours;
• Three weeks of vacation per year (15 working days);
• Paid sick leave per year (5 working days);
• Amazing opportunities for professional growth within a top-notch team of professionals;
• Competitive compensation commensurate with your experience and skills;
• English lessons;
• Co-working compensation;
• An excellent team with a friendly atmosphere.