Jobs ML / AI

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 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.

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

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).

AI Implementation Specialist (Remote) — Training & Client Placement Provided

We're building a team of AI Implementation Specialists who get trained on cutting-edge AI tools and placed directly inside US businesses to build automations, dashboards, tools, and systems.

What You Get:
- Free training through our AI certification program
- Placement with a paying US client
- Ongoing access to updated training as AI tools evolve
- The chance to build a real career in AI implementation

What We Need:
- Basic understanding of technology (you know what APIs, databases, and coding are)
- Experience with AI tools (ChatGPT, Claude, Midjourney, or similar)
- Comfortable learning new tools quickly
- Strong English communication (written and verbal)
- Self-motivated — you figure things out, you don't wait to be told

Nice to Have (Not Required):
- Command line / terminal experience
- Basic HTML/CSS knowledge
- Experience with automation tools (Zapier, Make, etc.)
- Any coding experience (Python, JavaScript, etc.)

This is NOT a traditional VA role. You won't be doing data entry or calendar management. You'll be building real AI systems inside businesses.

Why this role exists:

We are looking for an AI / Generative AI Engineer to join our AI team and contribute to LLM-based systems used in production.

In this role, you will work on Generative AI solutions such as chatbots, AI assistants, MCP-based services (Model Context Protocol servers), and other LLM-powered components. These systems support knowledge-driven workflows, AI-assisted interactions, and AI automation across the platform.

You will work within an existing ML and data platform, contributing to systems that are practical to operate, observable, and reliable. The role is hands-on and engineering-focused, with guidance from senior engineers and clear ownership boundaries.

This is not a research role and not limited to prompt writing. The focus is on building, integrating, and operating GenAI systems as part of real products and internal tools.

What you’ll drive:

• Implement and maintain LLM-based features and services under guidance;
• Build and improve chatbots and conversational AI systems with predictable behavior;
• Contribute to AI-assisted and AI-automated workflows that reduce manual effort;
• Work on RAG pipelines, including document ingestion, embeddings, retrieval, and generation;
• Implement parts of agent-style workflows (tool usage, step orchestration);
• Integrate GenAI components with existing backend services and APIs;
• Help monitor system behavior, performance, and basic quality metrics;
• Participate in debugging issues and supporting systems in production;
• Collaborate with Product, ML Engineering, and Backend teams;

• Follow team standards for code quality, testing, and documentation.

   

What makes you a GR8 fit:

• Solid background in software engineering;
• Hands-on experience with LLM-based systems or applications;
• Practical experience with: Large Language Models, RAG architectures and embedding-based retrieval, Chatbot or conversational system development, tool/function calling or structured LLM outputs;
• Familiarity with context or tool-serving patterns (e.g. MCP or similar concepts);
• Experience contributing to production systems;
• Basic understanding of performance, latency, and cost considerations;
• Experience working with cloud infrastructure (preferably AWS);
• Familiarity with evaluation or monitoring of AI systems;

• Strong engineering fundamentals (clean code, testing, debugging).

   

Tech Stack:

Experience with most tools listed below is expected, and openness to adopting new tools is part of the role.

Languages

• Python
• SQL (basic)

LLMs & GenAI

• Amazon Bedrock
• Third-party LLM APIs (e.g. OpenAI, Anthropic)
• Open-source models (LLaMA, Mistral/Mixtral, Qwen, or similar)
• Hugging Face ecosystem

Frameworks & Orchestration

• LangChain
• LangGraph
• Pydantic
• Langfuse

RAG & Retrieval

• Embeddings
• Vector stores: Qdrant, FAISS, OpenSearch, pgvector

Cloud & Infrastructure (AWS-first)

• AWS (ECS / EKS / Lambda)
• S3, OpenSearch
• API Gateway

Dev & Ops

• Docker
• Git
• CI/CD

About us:
 

BetterMe — a global wellness ecosystem empowering millions to become better — physically, mentally, and emotionally. We build what makes people better and keep challenging ourselves to inspire others.
 

Your impact:

• Build AI agents for engineers that transform development workflows
• Automate routine engineering tasks (requirements refinement, coding, testing)
• Improve team velocity and reduce manual effort through AI-driven solutions
• Create internal best-practices guidelines for building and scaling AI agents
• Act as an Engineering × AI multiplier across teams
   

About you:

• 1+ year of hands-on experience building and integrating AI/LLM solutions
• Strong Software Engineering, AQA, SDET or DevOps background
• Practical experience with Context Engineering and RAG architectures
• Experience building multi-agent systems (n8n, Claude Code, Agents SDK, etc.)
• Strong hands-on experience with coding agents (Cursor, Claude Code, Codex)
• Proven ability to operate autonomously and deliver measurable results
• Systems thinker with strong time management and ownership mindset
   

Will be a plus:

• Understanding of infrastructure fundamentals, including MLOps principles, cloud platforms (AWS/GCP), and Kubernetes.
   

What you get at BetterMe:
 

A mission that inspires. Every line of code, every design, every idea helps millions of people become healthier and more confident.

Trust without micromanagement. You manage your time and make decisions independently. We value outcomes, not online hours.

Growth opportunities. 90% of our leads have grown within the company. There’s space for initiative, new responsibilities, and real career upgrades.

Flexible work format. Choose what works best for you — office, remote, or hybrid.

Wellness in practice. Offline: workouts with professional trainers in our corporate gym, massage, corporate lunches, sports, and team activities — everything you need to recharge and reset together. Online: regular online workouts, partner discounts, and free access to our products.

Health insurance & corporate doctor.

Open communication. Transparency across teams, honest feedback, and support for initiatives are part of our everyday culture.

Support for sports events. We cover entry fees and encourage the team to compete and participate together.

Modern equipment. We provide new hardware and everything you need for productive work.

Legal & finance support. Experienced lawyers and financial specialists are always there to help — from documents to personal consultations.

The client is one of the largest global independent private equity fund administrators, administering over $300 billion of private capital on behalf of its clients with offices in New York, San Francisco, Boston, Stamford, Dallas, and Luxembourg. They offer private fund sponsors a best-in-class combination of people, process, and technology, enabling fund sponsors to most effectively manage their operational infrastructure, financial reporting, and investor communications.

The client represents the most experienced and longest-tenured team in the private equity fund administration industry, with broad expertise across buyout, funds of funds, real estate, energy, infrastructure, credit, co-investment, hybrid funds, feeder funds, venture capital, retail, and managed accounts.

The project aims to provide well-prepared and formatted analytic data for the customer.

Responsibilities: 

Own the architecture and delivery of LLM-powered chatbot solution for enterprise financial platform. Responsible for orchestration logic, prompt engineering strategy, model governance and technical leadership across AI components.

• Define LLM orchestration architecture (single-agent pattern)
• Design prompt engineering strategy and system prompting
• Define model behavior guardrails and safety controls
• Lead golden dataset validation strategy
• Own AI risk mitigation (hallucination control, determinism limits)
• Collaborate with BE/FE/DevOps on integration
• Technical leadership & code review for AI components

Requirements: 

• 3+ years in AI/ML engineering
• Hands-on with OpenAI / Azure OpenAI APIs
• Python experience
• Understanding of API-driven architectures
• Intermediate or higher level of English 

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

The client is one of the largest global independent private equity fund administrators, administering over $300 billion of private capital on behalf of its clients with offices in New York, San Francisco, Boston, Stamford, Dallas, and Luxembourg. They offer private fund sponsors a best-in-class combination of people, process, and technology, enabling fund sponsors to most effectively manage their operational infrastructure, financial reporting, and investor communications.

The client represents the most experienced and longest-tenured team in the private equity fund administration industry, with broad expertise across buyout, funds of funds, real estate, energy, infrastructure, credit, co-investment, hybrid funds, feeder funds, venture capital, retail, and managed accounts.

The project aims to provide well-prepared and formatted analytic data for the customer.

Responsibilities: 

Own the architecture and delivery of LLM-powered chatbot solution for enterprise financial platform. Responsible for orchestration logic, prompt engineering strategy, model governance and technical leadership across AI components.

• Define LLM orchestration architecture (single-agent pattern)
• Design prompt engineering strategy and system prompting
• Define model behavior guardrails and safety controls
• Lead golden dataset validation strategy
• Own AI risk mitigation (hallucination control, determinism limits)
• Collaborate with BE/FE/DevOps on integration
• Technical leadership & code review for AI components

Requirements: 

• 5+ years in AI/ML engineering
• Strong hands-on with LLM APIs Azure AI Foundry
• Prompt engineering in production systems
• Experience with RAG / structured API orchestration
• Understanding of AI governance & enterprise compliance
• Upper-Intermediate or higher level of English

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

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Lead Computer Vision & ML Engineer — Founding Role

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 Lead CV/ML Engineer as a founding member of the engineering team. This is not a role where you inherit a codebase and maintain it. You will define the ML architecture, choose the tools, build the pipeline from scratch, and grow a team around it as the platform matures.

The technical plan outlines the direction — petabyte-scale video processing, active learning, edge deployment on Jetson — but the specific implementation decisions are yours to make. We value strong technical judgement over checkbox experience with a predefined stack.

What You Will Own

ML Architecture & Technical Direction
- Define the end-to-end ML pipeline: from raw video ingestion through data curation, training, and deployment to UAVs
- Evaluate and select the tools and frameworks that best fit the problem (our current thinking: PyTorch, Ray, MLflow, FiftyOne — but nothing is set in stone)
- Establish training infrastructure, experiment tracking, and model versioning from day one
- Make build-vs-integrate decisions across the stack

Data Pipeline & Curation
- Design video preprocessing pipelines: clip segmentation, frame extraction, scene detection, embedding extraction
- Build a data curation workflow to select diverse, high-quality training subsets from a massive raw corpus
- Define the annotation ontology and labelling policy for detection, classification, and multi-object tracking

Model Development
- Train and iterate on computer vision models for object detection, scene classification, tracking, and segmentation
- Implement distributed multi-GPU training for large-scale experiments
- Design the active learning loop: auto-labelling with confidence routing, human review integration, retrain triggers
- Define quality control metrics and model promotion criteria

Edge Deployment
- Optimize models for real-time inference on NVIDIA Jetson (ONNX, TensorRT, INT8 quantization)
- Validate edge accuracy against training baselines
- Design the model delivery pipeline from registry to deployed UAVs

Team Building
- Hire and mentor ML engineers as the team grows
- Establish engineering practices: code review, testing, documentation
- Own the ML technical roadmap and communicate it across the company

What We Are Looking For

Must Have
- 5+ years in computer vision and deep learning, with production deployments
- Strong PyTorch proficiency, including distributed training
- Experience with object detection and tracking pipelines (YOLO family, RT-DETR, Detectron2, or similar)
- Hands-on model optimization for edge or mobile deployment (TensorRT, ONNX, SNPE, or similar)
- Experience building training infrastructure (pipelines, experiment tracking, CI/CD for ML)
- Proven ability to lead a small engineering team (hiring, mentoring, technical guidance)
- Python as primary language; clean, production-grade code

Strong Plus
- UAV / drone / robotics domain experience
- NVIDIA Jetson deployment experience
- High-performance video processing pipelines (DeepStream or custom)
- MilTech or defense-related work
- Experience defining ML architecture from scratch at an early-stage company
- C++ for performance-critical components

Proposed Tech Stack

This is our starting point, not a mandate. The right candidate will validate, adjust, or replace these choices based on their experience.

- 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

- A founding engineering role with direct influence on the technical direction of the company
- Ownership of the full ML pipeline end-to-end — from raw video to models flying on UAVs
- 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
- The opportunity to build and lead an ML team from the ground up
- Competitive salary
- Stock option
 

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

1 EM, 5 ML 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 other.
  • Experienced in natural language processing and modern LLM based techniques.
  • Experience with full ML lifecycle, data preprocessing, training, evaluation stages 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 express your thoughts in a professional manner 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 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.

Про компанію SPD TechnologySPD Technology is a custom software product development and IT consulting company with a world-class team of over 600 experts with extensive expertise in solving big-time technical challenges, efficiently managing large-scale software development efforts, and seamlessly integrating with the client’s business through tailored, long-term partnerships for delivering cutting-edge tech solutions that drive clients' growth.

Our major expertise includes 10 key industries: Fintech, E-commerce, Telecom / IoT, e-Learning, Logistics, Insurance, Biotech, Cybersecurity, Medicine, Wellness. Our top-notch engineering teams deliver Web, Mobile, AI/ML or Enterprise solutions for world-renowned businesses and budding startups. Our key clients are iconic brands such as PitchBook, MorningStar, Roche, and more. Ten of our clients report more than $100 million in annual revenue.

We have 3 development centers in Eastern Europe, and remote teams, working worldwide. With over 17 years of experience in designing, building, streamlining, and supporting software products, SPD Technology drives growth of businesses from the US, the U.K., Israel, Switzerland, Mexico, and other countries.

Let’s create empowering tech solutions together!