Jobs AI

The role

You'll be one of the first Account Managers we hire. You take ownership of a portfolio of ~50–75 paying customers — your job is to keep them happy, grow their revenue, and convert hot inbound leads into new paying accounts. You'll work directly with the Head of Customer Growth and the founders.
 

What you own

• Customer portfolio health — your assigned accounts stay active, healthy, and growing
• Expansion revenue — upgrades to higher plans, additional channels (WhatsApp / RCS / SMS), additional sender names
• Retention — proactively identify at-risk accounts, run save calls, recover them
• Referrals — turn happy customers into a referral pipeline
• Inbound conversion — hot leads that come in via our chat / website land on your desk; you discover, qualify, demo, and close
   

You're a fit if

• 2+ years in B2B SaaS Customer Success, Account Management, or Sales (NOT support / consulting / agency)
• Strong written and spoken English (C1+) — daily calls with US customers
• Comfortable with API / developer products (you don't code, but you understand what our customers build)
• Data-driven — you can read a CRM dashboard, articulate why a metric is moving, prioritize accordingly
• Self-starter — small team, no micromanagement
• Open and curious about AI tools  — we use them daily. 

Nice to have

• Worked at an API / infrastructure / dev tools SaaS 
• Direct experience with US-based B2B SaaS customers
• Already using AI tools in customer-facing workflows

What we offer

• $2,000 base + performance bonus (OTE $3,000 from Month 4)
• Remote. Direct collaboration with founders and Head of CS
• Modern stack
• Real ownership: your accounts, your numbers, your impact

Location: Remote

Time Zone: Europe (±2 hours)

Language: Fluent English (spoken and written)

About the Project
Our client is a Netherlands-based product company developing an intelligent platform that automates logistics and freight-forwarding processes through AI-driven solutions.

What You'll Do

 

• Design, develop, and enhance AI agents that automate logistics workflows
   
• Expand the capabilities of intelligent bots for customer support and commercial proposal generation
   
• Improve model reliability and reduce LLM hallucinations
   
• Build dashboards for both customers and internal teams
   
• Optimize and scale existing systems through refactoring and performance improvements
   

Technical Requirements

 

• Strong experience with Python and Django/FastAPI
   
• Solid understanding of OAuth 2.0, SSO, and REST APIs
   
• Experience with PostgreSQL (SQLAlchemy is a plus)
   
• Experience with Redis/RabbitMQ and Celery
   
• Hands-on experience with LLM-related tools and frameworks, such as:
   
• Ollama
   
• LlamaIndex
   
• LangChain / LangGraph
   
• Tool Calling
   
• Sentence Transformers
   
• Experience with:
   
• Pandas
   
• NumPy
   
• scikit-learn
   
• pytest
   
• Faker
   
• Experience working with email systems (parsing, generation, routing)
   
• Knowledge of prompt engineering or practical experience integrating LLM-based solutions
   

Nice-to-Have Skills

 

• Experience in logistics, freight forwarding, or supply chain domains
   
• Experience optimizing ML/LLM pipelines
   
• Knowledge of RAG architectures, FAISS, and Vector Databases
   
• Strong focus on code quality, maintainability, reusability, and stability
   
• DevOps experience with CI/CD, Docker, Docker Compose, and Kubernetes
   
• Hands-on experience with monitoring and observability using the Grafana stack
   

What We Offer

 

• The opportunity to build solutions that impact real-world business operations in a global industry
   
• Fast decision-making and the flexibility of a startup environment
   
• Direct influence on product direction and technology choices
   
• A collaborative team with an open and transparent culture

We are a global AI-powered financial intelligence company that leverages proprietary AI and large language models to deliver investment research and insights across global markets. Our platform enables financial institutions and investors to access transparent, explainable, and multilingual analysis across equities, funds, and other financial instruments.

We are building scalable, production-grade AI systems that make high-quality financial research accessible and data-driven.

We are looking for a Mid Data Scientist / AI Engineer to develop and deploy machine learning and AI solutions, with exposure to LLM-based systems and modern NLP applications. You will collaborate with senior engineers to build scalable and reliable AI-driven products.

Requirements:

• 3+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• 1+ year of experience with LLM and NLP-related tasks
• Understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Docker
• Strong knowledge of object-oriented programming
• Hands-on experience with RAG pipelines and vector databases
• Experience with cloud platforms (AWS, Google Cloud, Azure)

Join a Company That Invests in You

Seeking Alpha is the world’s leading community of engaged investors. We’re the go-to destination for investors looking for actionable stock market opinions, real-time market analysis, and unique financial insights. At the same time, we’re also dedicated to creating a workplace where our team thrives. We’re passionate about fostering a flexible, balanced environment with remote work options and an array of perks that make a real difference.

Here, your growth matters. We prioritize your development through ongoing learning and career advancement opportunities, helping you reach new milestones. Join Seeking Alpha to be part of a company that values your unique journey, supports your success, and champions both your personal well-being and professional goals.

What We're Looking For

Role Overview: We are developing Ask Seeking Alpha — a high-load financial analysis system based on Large Language Models. The architecture is built on complex multi-agent orchestration using LangGraph, FastAPI, and Elasticsearch.

We are looking for a Senior Backend Engineer specialized in Generative AI to design agent workflows, optimize interactions with models (OpenAI, AWS Bedrock), and ensure the reliability of non-deterministic systems in production.

The Senior Python AI Engineer will be engaged with the company as a contractor (Private Entrepreneur).

Tech Stack: Python (Asyncio), FastAPI, LangChain, LangGraph, Pydantic, Elasticsearch, AWS Bedrock / OpenAI API, LangSmith.

What You'll Do

• Agent Architecture: Design and implement complex agent orchestration logic using LangGraph. You will define state management, conditional routing, and error handling within the agent graph.
• Tool Engineering: Build and optimize the tool layer (function calling) that allows LLMs to interact with internal financial APIs and databases accurately.
• Performance Optimization:

-Reduce end-to-end latency through asynchronous processing and streaming (SSE).

-Implement semantic caching strategies to minimize API costs and response time.

-Optimize token usage without sacrificing answer quality.

• Observability & Evaluation: Implement automated evaluation pipelines using LangSmith. You will be responsible for setting up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment.
• Advanced RAG: Refine retrieval strategies. Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion to feed the most relevant context to the model.

Requirements

• Python Expert: Strong proficiency in modern Python. Deep understanding of asynchronous programming (asyncio) patterns is mandatory, as our entire I/O pipeline (Network, DB, LLM) is non-blocking. Experience with FastAPI and Pydantic (v2).
• Agentic Frameworks: Production experience with LangChain. Hands-on experience or deep conceptual understanding of LangGraph (or similar state-machine-based agent frameworks).

Deep LLM Expertise (What we mean by "Deep"):

• Non-determinism Management: Strategies for handling LLM hallucinations and ensuring reliable outputs (e.g., self-correction loops, specific prompting techniques like CoT/ReAct).
• Structured Outputs: Experience forcing LLMs to adhere to strict schemas (Pydantic/JSON mode) for reliable downstream processing.
• Context Optimization: Advanced strategies for managing limited context windows (summarization chains, sliding windows, selective context injection) beyond simple truncation.
• Inference Economics: Understanding the trade-offs between model size, latency, and cost (e.g., when to route to GPT-4 vs. a smaller/faster model).

Nice to Have

• Experience with Elasticsearch (DSL queries, analyzers).
• Knowledge of vector databases and embedding models.
• Background in FinTech or familiarity with financial data structures.

We are an international developer of IT products for medicine and related services. Our products are used by more than 5,000 doctors and more than 1,000 clinics in Europe.

The goal is to attract the largest possible audience to the main projects - clinics and doctors up to 3 million. As well as expanding unique traffic to 10 million per day until 2025. We are looking for AI Engineer / AI Architect with deep knowledge of Fundamental Mathematics, Probability Theory and Bayesian Statistics, Graph Algorithms, Mathematics of Transformers, Hybrid AI Approaches, Uncertainty Assessment.

Must-have skills are:
1. ML and Data Science (Core):
- Expert in NLP & LLM: Deep understanding of Transformers architecture (BERT, RoBERTa, GPT, T5, Llama/Mistral). Experience with Large Language Models (LLM) – not prompt engineering, but fine-tuning (PEFT, LoRA) of open-source models on specific datasets.
- RAG (Retrieval-Augmented Generation): Experience building RAG systems is required. The AI ​​must be able to search for information in different data sources.
- Named Entity Recognition (NER) & Information Extraction: Ability to extract specific entities from unstructured text.
- Tabular Data & Classic ML: Confident use of classical algorithms (XGBoost, CatBoost, LightGBM) for analyzing structured data and building probability scoring models.
- Frameworks: PyTorch (preferred) or TensorFlow/Keras. Proficiency in HuggingFace, Scikit-learn, Pandas, and NumPy.

2. MLOps:
- Experience wrapping models in APIs (FastAPI, Flask) with minimal latency. 

- Docker knowledge and experience working with local GPU instances are required.
- Experience working with vector databases (Pinecone, Milvus, Qdrant, ChromaDB) for quickly searching for similar cases or working with knowledge bases.

- ML Pipelines: Experience building model training and retraining pipelines (Airflow, MLflow, DVC).

3. MedTech and Security:
- Practical working experience with sensitive personal data and GDPR/DSGVO requirements.

- It is important to be able to deploy and optimize local models (Llama 3, Mistral, Mixtral) within a closed company environment to ensure data privacy.
- Skills in quantization and distillation of models to speed up work without significant loss of quality.

Nice-to-have skills:
- Experience working specifically with medical data (EHR, EMR; HL7, FHIR, ICD-10/11 standards). 

- Knowledge of Interpretability/Explainable AI (XAI) methods. The end user should understand why the AI ​​suggested a particular option (SHAP, LIME).

- Experience with multimodal models.

What we offer:
- Paid holiday for 28 working days.
- Transparent incentive system.

Working with us means:
- Unique technological and innovative projects.
- Gaining experience in modern western world practices in security, scalable architecture, etc.
- In-depth knowledge of telemedicine.
- Working with Big data, high load, distributed computing and data buses.
- Socially important projects.
- Opportunity to influence both technology and product solutions.
- Profitability and stability of a large European company.

We seek a Strong Middle ML / AI Engineer to join our team on a humanitarian transparency platform. This is a hands-on engineering role focused on building machine learning models and data pipelines — primarily around deduplication, anomaly detection, and statistical analysis of humanitarian data.

 

🧙‍♂️ In This Role You Will

• Design, build, and maintain ML models for deduplication, anomaly detection, and predictive analytics.
• Work with structured humanitarian data — beneficiary records, financial transactions, procurement flows.
• Build and maintain data processing pipelines using Python (Pandas, NumPy, scikit-learn).
• Collaborate with the backend team to expose ML/AI outputs via APIs.
• Monitor model performance and iterate based on real-world feedback.
• Document your work and support knowledge sharing within the team.
  
  
   

🎯 You May Be Interested If

• You enjoy working with messy, real-world data and turning it into reliable ML outputs.
• You care about model quality, reproducibility, and practical impact.
• You're comfortable applying classical ML approaches to solve concrete business problems.
• You're excited to collaborate in a remote, cross-functional environment.
• You value autonomy, clear communication, and working in a supportive, small-team setting.
  
   

👌 Role Requirements

• 3+ years of experience in ML engineering, data science, or a closely related role.
• Strong Python skills: Pandas, NumPy, scikit-learn.
• Experience building and deploying ML models in production environments.
• Solid understanding of data pipeline design and data quality practices.
• Familiarity with cloud platforms (Azure or AWS) for ML workloads.
• Proficiency with Git and standard development tooling.
• English proficiency at B1 level or higher.
   

Nice to have:

• Experience with PyTorch or TensorFlow.
• Hands-on experience with LLM integrations (OpenAI, Anthropic, or similar).
• Familiarity with ML experiment tracking tools (e.g. MLflow, Weights & Biases).
• Experience with GIS or geospatial data.
• Background in fraud detection, entity resolution, or deduplication tasks.
• Familiarity with Docker and CI/CD workflows for ML pipelines.
  
   

💻 Working Conditions

• Employment Type: Full-Time
• This is a fully remote position with the entire team across Ukraine.
• 20 working days of paid vacation per year.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• Flexible working hours to promote a healthy work-life balance.

Ever worked on systems where software has to process large amounts of data, integrate multiple external sources, and deliver reliable results in real time?

Where performance, scalability, and engineering quality matter just as much as building new functionality?

Where you're trusted to design solutions, challenge technical decisions, and take ownership of complex backend systems?

If you enjoy building production-grade platforms, working with modern AI technologies, and solving difficult engineering problems — we'd love to talk.

About the Company

Our client is a Switzerland-based technology company building data-intensive platforms and analytical systems used across multiple industries, including financial technology, geospatial intelligence, and security-focused applications.

The company develops products that combine large-scale data processing, AI-powered workflows, real-time analytics, and advanced visualization tools.

The Role

We're looking for a Senior Software Engineer who can own complex backend systems while collaborating closely with frontend, data, and AI teams.

You'll work across Python services, data pipelines, AI integrations, and modern web applications, helping design scalable solutions and improve system performance as the platform continues to grow.

What You'll Do

Backend & Platform Development

• Build and maintain services using Python, FastAPI, and asyncio
• Design scalable architectures with PostgreSQL, Redis, and Celery
• Develop APIs and integrations with external data sources

Data & AI Systems

• Build ETL pipelines and data processing workflows
• Integrate OpenAI and Anthropic APIs
• Develop RAG-based solutions and work with vector databases (pgvector, Qdrant, Weaviate, Pinecone)
• Process and analyze data using Pandas and NumPy

Performance & Engineering Quality

• Optimize system performance, database queries, and background jobs
• Identify bottlenecks and improve scalability
• Participate in architecture discussions and code reviews

Cross-Functional Collaboration

• Work with Next.js and TypeScript-based applications
• Support data visualization and dashboard features

• Collaborate closely with product and engineering teams

   

What You Bring

• Strong commercial experience with Python, FastAPI, asyncio, Celery
• Experience with PostgreSQL, Redis, and worker-queue architectures
• Hands-on experience building ETL pipelines and data-intensive applications
• Experience integrating LLMs and working with RAG architectures
• Experience with vector databases
• Strong understanding of performance optimization and scalable system design
• Upper-Intermediate English or higher

Nice to Have

• Next.js and TypeScript experience
• Cybersecurity or infrastructure security background
• Experience with Matrix, Signal, GrapheneOS, or hardened Linux environments
• Penetration testing or offensive security knowledge
• Fintech, trading, or other high-reliability systems experience

What You Get

• Engineering-First Environment: Work with teams that care about architecture, maintainability, and technical correctness - not just feature velocity.
• Real Technical Influence: Your feedback will directly impact engineering standards, code quality, and technical decisions.
• Complex Systems: Trading infrastructure, async workflows, performance-sensitive systems, and real-world scalability challenges.
• Direct Communication Culture: The company values honest technical feedback, critical thinking, and engineering maturity over hierarchy or corporate formalities.
• Strong Autonomy: No micromanagement. Engineers are trusted to make technical judgments and take ownership.

Interested?

Apply now if you're excited about building scalable Python platforms, AI-powered workflows, and data-intensive systems that operate in production at scale.

CodeTiburon is looking for an AI Research Engineer — Neuro-Symbolic Reasoning & Generative AI to join our team and work closely with one of our long-term clients.
 

About the Project

Our client is an applied AI lab specializing in formal knowledge representation and next-generation reasoning. The project is dedicated to building “semantic AI” capable of deep, grounded reasoning over complex structures such as texts, arguments, and intellectual traditions.
 

The core mission is to combine the power of modern LLMs with the rigor of neuro-symbolic methods and Knowledge Graphs. By focusing on domains with the highest logical standards, the team aims to set new benchmarks for responsible and intelligent AI behavior across the industry.
 

About the Role:

You will be employed by CodeTiburon and embedded into the client’s research team on a long-term basis. Working alongside a Senior Applied Scientist, you will help transform research ideas into production-quality systems and reproducible experiments.

While the Applied Scientist defines research directions and designs novel algorithms, you will be responsible for implementing experiments, fine-tuning models, building evaluation frameworks, developing data and reasoning pipelines, and iterating toward robust, production-ready solutions.

You will serve as a key engineering partner in the research process—proposing implementation strategies, identifying engineering constraints early, and translating hypotheses into measurable results.

 

Topics You Will Work On:

• Experiment Implementation. Translate research designs from the Applied Scientist into clean, reproducible Python experiments—covering neuro-symbolic architectures (LTN, DeepProbLog, LARK), hybrid LLM+KG pipelines, and RAG systems.
• Knowledge Graph & Ontology Engineering. Build and maintain tooling around RDF/OWL 2 ontologies, SPARQL/Cypher queries, and graph databases (Neo4j, Amazon Neptune) to feed downstream reasoning modules.
• RAG/KG Pipeline Development/Integration. Implement and iterate on retrieval-augmented generation/KG pipelines—combining dense, sparse, and structured retrieval over heterogeneous corpora with provenance tracking.
• LLM Fine-Tuning & Evaluation. Run supervised and RLHF/DPO fine-tuning experiments; build evaluation harnesses that include symbolic verification layers, benchmarks, and regression suites.
• Research Infrastructure. Own the experiment tracking, dataset pipelines, and MLOps scaffolding (MLflow, SageMaker, Vertex AI) that let the team iterate quickly and reproduce results reliably.
• Literature & Prototyping. Stay current with relevant publications; rapidly prototype ideas from newly published methods and assess their fit against the client’s goals.
  
   

Required Qualifications
 

Education:

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, AI Planning, Machine Learning, Cognitive Science, Formal methods, or a closely related field.
 

Language Skills:

Professional working proficiency in English, both written and spoken, with the ability to participate in technical discussions, read and implement research papers, document findings, and collaborate effectively in an international research environment (Strong B2/C1).

Core Technical Skills:

• Generative AI / LLMs: solid working knowledge: transformer architecture, prompt engineering, RAG, tool use, fine-tuning (SFT/LoRA);
• Machine Learning: proficient: supervised/unsupervised learning, representation learning, experiment design;
• Neuro-Symbolic Concepts: familiar: exposure to at least one framework (s.t. LTN, DeepProbLog, NSCL, LARK) or symbolic AI coursework; eager to deepen;
• Knowledge Graphs: working knowledge: graph data models, SPARQL or Cypher queries, at least one graph DB (Neo4j or equivalent);
• Software Engineering: strong production Python; unit testing, version control, CI basics
   

Experience:

• Proven ability to independently implement research ideas, build reproducible experiments, and contribute to production-ready AI systems.
• Demonstrated ability to implement models and algorithms from research papers with minimal hand-holding.
• 3–5 years of hands-on experience in ML/AI engineering, research engineering, or a closely related role (internships and research assistant positions count).
• Experience with experiment tracking tools (MLflow, Weights & Biases, or similar) and reproducible research practices.
• Experience working with cloud-native ML infrastructure on AWS, GCP, or Azure.
   

Preferred Qualifications:

• Exposure to formal knowledge representation: OWL 2, RDF/RDFS, description logics, or first-order logic formalisms.
• Familiarity with agentic AI frameworks (tool-use chains, multi-step planning, multi-agent coordination).
• Experience with LLM evaluation and red-teaming for factual accuracy, logical consistency, or safety.
• Contributions to open-source ML/NLP/KR projects or co-authorship on an arXiv pre-print or workshop paper.
• Exposure to formal verification, SAT/SMT solvers, or answer set programming.
• Experience with low-resource or domain-specific fine-tuning of foundation models.
• Familiarity with graph neural networks or heterogeneous graph transformers.
• Experience with AI coding tools such as Claude Code or Cursor.
• Proven ability to deliver production-ready artifacts.
   

Responsibilities:

• Implement, run, and iterate on experiments designed by the Applied Scientist; maintain clean, well-documented, reproducible code.
• Build and maintain RAG pipelines, knowledge graph integrations, and neuro-symbolic prototype systems.
• Design and execute evaluation harnesses—combining automated metrics, symbolic checks, and human evaluation—to measure model quality and catch regressions.
• Keep experiment infrastructure (data pipelines, tracking, compute provisioning) reliable and easy for the whole team to use.
• Read relevant papers and proactively surface implementation options or potential issues before they become blockers.
• Collaborate daily with the Applied Scientist, ML engineers, and content teams to align research outputs with product requirements.
• Contribute to internal documentation, design reviews, and code reviews; grow your skills through mentorship from senior researchers.
• Uphold scientific rigour, reproducibility, and responsible AI practices in every piece of work you ship.
• Working closely with the production owners.

If this sounds like you and your experience aligns with most of the qualifications above, we’d love to hear from you. Please send us your CV.

Thank you for your interest. Each application is carefully reviewed, and candidates whose experience and background best align with the role will be contacted regarding the next steps.

Job Summary
As a Software Engineer, you will work directly with AI coding models to evaluate their performance, identify weaknesses, debug incorrect outputs, and create stronger alternative solutions. This role is ideal for developers who enjoy problem-solving, code analysis, and improving how AI understands and generates technical answers.

Key Responsibilities

• Work with Frontier Labs, producing training data to train Al models. 
• Test and evaluate agentic coding models designed to perform complex engineering tasks at a senior developer level.
• Focus on creative problem-finding rather than traditional feature shipping. 
• Ideal candidates use AI, enjoy problem-solving, and like "outsmarting" Al systems. 

Requirements

• 3–4 years of hands-on experience as a Full Stack Developer on commercial projects, including B2B SaaS systems and data-heavy applications.
• Use AI tools (AI agents, Claude Code, Cursor, Codex or similar) in daily workflow.  
• Strong judgment across the full software lifecycle:
  • Reading a PRD and breaking it into Jira tickets
  • Estimating effort and scoping work
  • Architecture and design choices
  • Reviewing PRs
  • Debugging and recovering when blocked
• Strong proficiency with React.js and Node.js, with experience using Express.js or NestJS to build scalable backend systems that support complex business logic.
• Experience designing and integrating REST APIs. 

• Upper-Intermediate English (B2) for effective communication and technical discussions.

   

You will be part of building better AI systems by helping improve the quality, accuracy, and reliability of the answers they provide. If you want to use your engineering skills in a fast-growing AI field, this role is a strong opportunity to contribute to the future of AI-assisted development.

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

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

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

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

About the position

Quantum is expanding the team and has brilliant opportunities for a Senior DS / AI Engineer. The client is a technological research company that utilises proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become "super-investors." Through our generative AI technology implemented into brokerage platforms and other financial institutions' infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.

Must have skills:

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and software engineering fundamentals
• Strong understanding and experience in the development of high-load production systems
• 2+ years of experience with LLM and NLP-related tasks
• Hands-on experience with RAG and vector DBs
• Knowledge of modern DL architectures
• Experience with at least one of the Deep Learning frameworks (Tensorflow, PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Strong experience in development with AI tools (Claude Code, Cursor)
• At least an Upper-Intermediate level of English (spoken and written)

Nice to have skills:

• Familiarity with MCP (Model Context Protocol)
• Experience with production LLM frameworks (vLLM)
• Experience in training LLMs
• Experience with Cloud Computing Platforms (AWS, GCloud, Azure)
• Participation in Kaggle competitions

Your tasks will include:

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

We offer:

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

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

About the Role

We are looking for a strong engineer who can help us build AI-powered tools and automation for real business problems.

We work with large amounts of business data and are building internal systems for verification, enrichment, and automation. We need someone who can quickly understand a problem, suggest a practical solution, and build it.

This role is very hands-on. We are looking for a builder — someone who likes solving problems, moving fast, and turning ideas into working products.

What You’ll Do

• Build AI agents and automation workflows
• Work with LLMs (OpenAI, Claude, etc.)
• Build tools that help automate manual work
• Integrate APIs and external systems
• Improve speed, quality, and reliability of workflows
• Quickly test ideas and move them into production
• Work closely with business and product teams

What We’re Looking For

Must Have

• Strong Python skills
• Experience building real products, systems, or automation
• Experience working with LLMs and AI tools
• Experience with APIs and integrations
• Ability to solve problems independently
• Fast execution and ownership mindset

Strong Plus

• Deep experience with AI-native development workflows
• Daily use of Claude Code, Codex, Cursor, or similar agentic coding tools
• Experience building products using AI-assisted engineering environments

Nice to Have

• Experience with LangGraph, CrewAI, AutoGen, or similar frameworks
• Experience with RAG, vector databases, or AI memory systems
• GitHub or personal projects
• Experience working with large amounts of data

Important

We are not looking for someone who only builds no-code automations.

We are looking for someone who can understand a business problem, think through the solution, and build working systems.

Please share examples of projects you built and your GitHub (if available).

We Offer

• Remote work
• Long-term collaboration
• High-impact projects
• Modern AI tools and technologies
• Fast-moving environment

The company is seeking a creative and detail-oriented Tech Art Auditor to join a team dedicated to producing engaging mobile game ads using cutting-edge AI technology. This role focuses on reviewing, refining, and enhancing AI-generated 2D and 3D assets to ensure high-quality visual output for mobile game advertisements.
 

This is an excellent opportunity for candidates eager to gain hands-on experience in tech art, 3D/2D production, and AI-assisted content creation within a dynamic and fast-paced environment.

 

What You’ll Do:
 

• Evaluate AI-Generated Content
  Review AI outputs, spot imperfections, and provide actionable feedback to improve overall quality.
• 3D Editing in Blender
  Modify and optimise low-poly 3D models, adjust shading, and ensure assets are production-ready.
• 2D Image Editing & Asset Creation
  Edit images, create visual elements, and prepare polished assets for mobile game ads.
• Work With Generative AI Tools
  Use AI-driven software to generate, refine, and enhance art assets efficiently.
  
   

What You’ll Bring:
 

Core Skills Required:

• Blender expertise for model editing, shading, and optimisation
• 2D editing proficiency (image editing & asset creation)
• Familiarity with generative AI tools and workflows
• Strong attention to detail and ability to critique, refine, and polish visual assets
• Passion for mobile gaming - especially casual and mid-core titles
  
   

Why This Role Stands Out:
 

• Work with innovative AI technologies shaping the future of game advertising
• Join a creative, fast-moving environment that encourages experimentation and growth
• Build valuable experience across 3D, 2D, and AI-driven art production
• Ideal for candidates at the beginning of their tech art career who want meaningful, practical hands-on experience
• Long-term cooperation, B2B collaboration, remote flexibility, and loyal management
  
   

Why You Should Submit Your CV & Contact Information:
 

To be considered, candidates must leave their CV and contact details so the team can:

• Evaluate your technical skills and portfolio
• Match your experience to the right projects
• Invite you for next-step discussions
• Keep in touch regarding future AI-art opportunities
  
   

Leaving your CV ensures you don’t miss out on a role that can accelerate your growth in tech art and AI-assisted asset creation.

OneAcademy is looking for a Video Designer with strong motion design skills and hands-on experience using AI tools for commercial video production. We are building a fast-scaling education brand focused on high-performance digital content, and we need someone who can combine creativity with speed and ownership.

What You’ll Do

• Create short-form video content (Reels, YouTube Shorts, TikTok) using AI-assisted production tools
• Develop static creatives for social media and marketing campaigns
• Optimize video production workflows to improve speed, efficiency, and scalability
• Adapt content to different platforms and formats
• Work within tight deadlines while maintaining quality standards

Hard Skills & Experience

• 2+ years of strong, hands-on experience with Adobe After Effects
• Basic proficiency in Adobe Photoshop
• At least 6 months of practical experience using AI tools for commercial video production (e.g., Kling, VEO, Sora, or similar)
• Experience with prompt engineering and cost optimization of AI tools (tokens / credits management)
• Solid understanding of composition, color correction, and storytelling fundamentals

Soft Skills We Value

• High level of independence and self-management
• Strong sense of responsibility and ownership over tasks and results
• Proactive mindset
• Fast learner, comfortable adapting to new tools and workflows
• Ability to operate in a performance-driven environment

What We’re Looking For

This role is ideal for someone who is not just an executor, but a creator who understands both aesthetics and performance metrics. You should be comfortable experimenting with AI tools, iterating quickly, and continuously improving production efficiency.

If you thrive in a fast-moving, digital-first environment and want to shape the visual language of a growing education brand — we’d love to hear from you.

Why OneAcademy

• Direct ownership over growth of a core educational product
• Opportunity to build a scalable, data-driven education business
• Global product with long-term LTV focus
• High level of autonomy and fast execution
  
  What We Offer
• Ownership of acquisition strategy 
• Work with large budgets and high-scale performance campaigns
• Direct influence on unit economics and growth metrics
• Opportunity to build and shape your own team
• Remote work with flexible schedule
• Work in a fast-growing global prop trading firm
• Performance bonuses and incentives

About the client:

Our customer is the European online car market, with over 30 million monthly users and a presence in 18 countries. As a Lead FullStack Engineer, you will play a pivotal role in shaping the future of online car markets and enhancing the user experience for millions of car buyers and sellers.

Responsibilities:

• Developing fast, high-traffic public-facing websites
• Explore new technologies and help the team to use them
• Work using AI tools and apply them to the SDLC
• Following software development best practices while delivering the work
• Following testing principles while testing your own code to ensure production readiness
• Follow the philosophy of: you-build-it-you-run-it (be responsible for the SDLC processes) 

Requirements: 

• 5+ years developing reliable, highly available, and scalable software systems
• Strong understanding of software architecture and design patterns
• Firm grasp of clean code principles and coding standards
• Strong proficiency using AI tooling, such as ChatGPT/Codex, for rapid development

Experience integrating AI tooling into your development environment for streamlined usage

• Experience with AI Frameworks like Vercel AI SDK, LangChain, etc.
• Strong proficiency with backend development with C# 
• Strong proficiency with TypeScript
• Strong proficiency with SQL& NoSQL datastores (GraphQL, Redis)
• Strong proficiency with frontend development (HTML, CSS, JavaScript)
• Strong proficiency with component-based frameworks and SSR (Next.js/React or Vue.js) or Angular with the desire to learn React/ Vue.js.
• Hands-on experience developing and maintaining 3rd party content management systems
• Knowledge of modern cloud infrastructures and tools, such as AWS, Terraform, and Docker
• Experience with APIs and developing in a service-based application environment
• Experience building optimized UIs for performance
• Proficiency with version control systems such as Git
• Experience working within a formal CI/CD pipeline
• Experience with logging, monitoring, and alerting services like Datadog, Newrelic
• Solid approach to testing and ensuring quality of code, Unit testing, backend, and frontend

At least Upper-intermediate English level

• This role requires mandatory timezone coverage: work must align with the Toronto (ET) timezone for LATAM hours and 13:00–21:00 EET for EU hours approximately.

We offer*:

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

*not applicable for freelancers

HYGO is a media and AI company that creates AI-generated content, builds AI influencers, and manages a social media network of over 100 million followers.

We're hiring multiple AI Prompt Engineers (Junior & Senior) to discover, test, and systematize prompts and creative strategies that produce viral, high-performing AI influencer content.

Focus: Discovering, testing, and systematizing prompts and creative strategies that produce viral, high-performing AI influencer content on Studio

Salary range:

• Junior: $40,000–$60,000 base + performance bonuses

• Senior: $70,000–$100,000 base + performance bonuses

Remote (open to relocation to Las Vegas, NV)

Why this role:

Studio's AI influencers live or die by their content. The images, videos, and media they post need to stop thumbs, spark engagement, and build audiences — and all of it starts with how the AI is prompted. Right now, prompt discovery is ad hoc. We need dedicated people whose entire job is to push the platform to its limits: finding the prompts that produce stunning content, the feature combinations that unlock new creative possibilities, and the repeatable strategies that any operator can pick up and run with. You're not engineering software — you're engineering virality.

The best prompt engineers will shape how every AI influencer on the platform creates content. Your discoveries won't stay in a doc — they'll become structured, modular prompt templates built into the product for all operators and users to adopt.

What you'll do:

• Spend the majority of your time inside Studio, systematically exploring every feature, parameter, and creative workflow to discover what produces the most compelling, viral-ready AI content

• Develop and test prompt strategies across content types — portraits, lifestyle shots, trending formats, video content, and any new media capabilities as they ship

• Discover powerful feature combinations — mixing generation modes, editing tools, style controls, and post-processing in ways that produce results greater than the sum of their parts

• Evaluate every discovery against social media performance criteria: will this stop a scroll? Will this get shared? Will this build an audience? If you can't answer those questions, the prompt doesn't matter

• Build structured, modular prompt templates — reusable formats with clear parameters that operators and users can adopt without needing to understand the underlying craft. Think of these as recipes: specific enough to produce consistent results, flexible enough to adapt to different influencer personas and content niches

• Design prompt architectures that could be productized — your best work will inform structured prompt builders within Studio, giving all users access to sophisticated prompting without requiring expertise

• Document and categorize discoveries by use case, content type, difficulty level, and expected performance — building a living library of proven strategies

• Stay obsessively current on social media content trends — what's performing on Instagram, TikTok, X/Twitter, Facebook, and YouTube — and translate those trends into prompt strategies before competitors catch on

• Test and iterate relentlessly — run A/B comparisons between prompt variations, track what works across different audience types, and refine strategies based on real-world content performance data

What we're looking for:

• The most important quality: social media fluency. You must have a deep, intuitive understanding of what performs on social media — what gets engagement, what gets shared, what builds audiences, and what falls flat. Without this, no amount of creativity or analytical ability matters.

• Strong understanding of social media content performance across major platforms — you can look at a piece of content and predict whether it will perform before it's posted. You follow trends obsessively and understand why things go viral, not just that they did

• Creative and experimental mindset — you're the kind of person who spends hours tweaking variables to see what happens. You find the edges of what a tool can do and push past them

• Systematic thinking — you don't just find one great prompt, you figure out why it works and build a repeatable framework around it. Your discoveries are structured and teachable, not one-off lucky shot

Interview stages:

1. Written Pre-screen (4-5 calibration questions from the team)
2. Call (Culture fit & Domain expertise/technical depth).
3. Test (Take-home or live assessment to see actual work mechanics)
4. Call (Test review & decision walkthrough) + 3 professional references required