Jobs at Djinni

We are looking for a Treasury Specialist to manage treasury operations within the company. This role combines technical tasks (executing payments, preparing registers) with organizational responsibilities such as opening accounts, managing compliance procedures, working with payment solutions, and collaborating with both internal and external stakeholders. You will work closely with the legal and finance teams to optimize processes and provide expert financial support.

Key Responsibilities:

Execute payments (manual and bulk through banking systems) and communicate with banks.

Open and manage company bank accounts.

Analyze the market for international banking and payment services.

Handle KYC procedures, prepare and provide required documents for banks and payment systems.

Manage cash flow across the group of companies and prepare cash flow budgets.

Prepare invoices and participate in billing processes.

Execute cryptocurrency payments.

Investigate problematic transactions and coordinate refunds.

Verify transactions for different teams, issue and manage corporate cards.

Assign and track payment-related tasks in Jira.

Requirements:

Education & Qualifications

Bachelor’s or Master’s degree in Finance, Accounting, Economics, or related fields.

Experience & Technical Skills:

At least 2 years of experience in treasury operations, cash management, or financial operations.

Strong knowledge of international banking systems (SWIFT, SEPA) and alternative payment providers.

Experience with manual payments and bulk register imports across banking platforms.

Understanding of KYC and compliance procedures.

Proficiency in Excel and financial planning tools (cash flow modeling, forecasting).

Basic knowledge of foreign exchange operations.

Soft Skills:

Excellent communication and negotiation skills.

High attention to detail and accountability.

Ability to work under pressure and meet deadlines.

Problem-solving mindset with a proactive approach.

Nice to have:

Experience working with non-resident structures and international bank accounts.

Familiarity with cryptocurrency payments and wallets (USDT, USDC).

Experience with ERP systems (e.g., MS Business Central).

We Offer:

A professional and supportive team.

A corporate culture where your opinion matters.

Flexible working hours and a hybrid (remote) work format.

20 paid vacation days.

Paid sick leave.

Maternity/paternity leave.

This position is open exclusively to Ukrainian residents within Ukraine (preferably Kyiv).
 

We are looking for a Business Analyst to partner with the Product Manager in enhancing and developing ERP, DSS and HRM systems.

Your focus will be on analysing business processes, capturing and formalising requirements, producing clear technical documentation, and ensuring smooth communication across all stakeholders.
 

Key responsibilities

• Work alongside the Product Manager on ERP, DSS and HRM systems to gather and manage business requirements.
• Analyse business processes, spot areas for improvement and propose solutions.
• Work with STANAGs, government standards and other regulatory documentation, and to extract requirements from them.
• Produce clear documentation (BRD, PRD, User Stories, Use Cases, User Journeys, technical specs).
• Map and visualise processes (BPMN, UML, Flowcharts).
• Collaborate with development and UX/UI teams to deliver effective solutions.
• Keep documentation up to date as products evolve.
• Engage with clients and stakeholders to collect feedback.
• Coordinate with Product Managers from other product areas to ensure aligned decision-making.
• Test new functionality and support users during roll-out.
   

Requirements

• 2+ years’ experience as a Business Analyst or in a related role.
• Practical experience with ERP, DSS and HRM systems.
• Background in manufacturing, logistics, finance, accounting, or e-government.
• Experience preparing clear technical documentation (User Stories, PRDs, specifications).
• Skilled in business process modelling (BPMN, UML).
• Experience with Agile/Scrum methodologies.
• Knowledge of SQL/BI tools.
• Ability to manage and structure large volumes of information.
• Excellent written and verbal communication, with the ability to present information clearly and concisely.
• Analytical mindset with the ability to untangle complex processes.
• Strong attention to detail and readiness to refine documentation.
• English level B2.
   

You’ll feel comfortable working with us if you:

• Have a good sense of humour.
• Use the BLUF approach (Bottom Line Up Front) in communication.
• Are familiar with military-style collaboration practices and ready to work accordingly.
• Are comfortable regularly updating documentation based on feedback.
   

Hiring process

1. Resume review — up to 5 business days.
2. Test task.
3. Intro call with the Head of Product.
4. Tech interview with several team members.
5. Offer discussion.
    

We offer

• Competitive compensation.
• Hybrid work model: a mix of office and remote work as needed.
• Paid vacation — 21 business days per year.
• Paid sick leave.
• Involvement in mission-critical projects.
• Exposure to intersecting domains: software development, information security, and cloud/on-prem infrastructure engineering.
• Experience in mission-critical projects.

Company Overview: 

Good Face is a formulation, regulatory compliance, and innovation software used by hundreds of leading cosmetic companies to make safe, compliant, transparent, and effective products. Our innovative solution cuts tedious work out of the product development and R&D cycle, enabling formulators to focus instead on product innovation and business growth. We are seeking a highly motivated and results-driven Cosmetic Chemistry and Regulations Data Analyst to join our dynamic Engineering team and contribute to our continued success. We are an ambitious, talented, and most importantly, fun team, with the common goal of bringing gamechanging technology to the beauty industry and enabling cosmetic chemistry innovators to build better beauty. Does collaboration, customer centricity, and relentless innovation sound like your workplace trifecta? 

Position Overview: 

As a Data Analyst, you will play a key role in delivering fresh cosmetic chemistry and regulatory data and insights into our core product in a repeatable and scalable way. You will be responsible for working together with the Cosmetic Chemist, Product, and Engineering teams to outline optimal data refresh flows, create systems/automations for monitoring the sources Good Face refers to, and to clean up and restructure the data so it becomes usable. By leveraging excellent analytical and process engineering skills, you will aim for process repeatability, rather than “one-and-done” data sourcing and analyses, enabling the delivery of excellent new and evolved product features while decreasing the amount of manual manipulation and data input required from the Cosmetic Chemist team, and from our End Users.

What you’ll be doing: 

● Scrape data from public sources of Cosmetics Regulations and ingredient inventories. 

● Clean, normalize, and perform basic analysis using Python libraries (e.g., pandas, numpy) 

● Store structured and unstructured data in PostgreSQL and MongoDB. 

● Collaborate with product and analytics teams to support regulatory and data enrichment projects and processes. What you’ll bring to the team: 

● Proficiency in Python for scraping. 

● Experience working with REST APIs 

● Hands-on experience with PostgreSQL and MongoDB 

● Strong data analysis skills using Python (pandas, numpy, matplotlib, etc.) 

● Experience working with scientific or regulatory datasets 

● Familiarity with basic ETL processes 

● Knowledge of automation/orchestration tools 

● English language proficiency 

If you are a proactive and ambitious individual who is passionate about connecting businesses with solutions, we would love to hear from you. Join our team and contribute to revolutionizing the way cosmetic brands thrive in the digital era.

Unfortunately, my buddy was sent to the front to protect the borders. 

After working together for three years, I'm now looking for a designer that can assist us with high quality designs—specifically for our b2b marketing campaigns. 

This involves building upon existing brand material for B2B companies. I'm looking for somebody that can be online in our Slack and work asynchronously. We don't need to speak; everything can be handled over chat, so your level of English writing should be good. 

I'm looking for somebody that can help with, web pages, brochures, pitch decks, and anything imaginable within Figma. We also sometimes do animations using Jitter. 

Please share your previous work. I'm looking for somebody that can really design modern, high-quality pages and material—somebody that works fast. Our focus is "good over perfect." I prefer speed over constant discussion about options :) 

 

Skills: 
 

• Brand design b2b
• UI design / UX thinking 
• Figma expert
• Friendly/fun personality :)

We are looking for a skilled DevOps Engineer to join our client's team on-site in Vilnius. If you are passionate about building and running reliable infrastructure, thrive in a hands-on environment, and enjoy working with both on-prem and cloud technologies, this role is an excellent opportunity for you!

Responsibilities:

• Design, build, and maintain bare-metal and Proxmox clusters running Ubuntu.
• Manage and harden Kubernetes clusters (HA control plane, upgrades, RBAC, network policies).
• Operate Kafka, PostgreSQL, and Redis in production (scaling, failover, observability, backups).
• Build and improve CI/CD pipelines with Azure DevOps.
• Automate provisioning, configuration, and operations using Terraform/Ansible or similar tools.
• Implement and maintain monitoring/alerting with Prometheus, Grafana, and logging solutions.
• Ensure infrastructure security (secrets management, patching, least privilege).
• Collaborate with developers to improve deployment workflows and system reliability.

Requirements:

• Strong background in Linux administration (Ubuntu/Debian) on bare metal and virtualization (Proxmox or similar).
• Proven hands-on experience with Kubernetes in production environments.
• Experience running and managing Kafka, PostgreSQL, and Redis.
• Scripting skills in Bash/Python and solid Git workflows.
• Experience implementing monitoring, logging, and observability solutions.
• Good command of English (spoken & written).

Nice to Have:

• Experience with Azure DevOps pipelines.
• Infrastructure as Code at scale (Terraform/Ansible modules, pipelines, policies).
• Knowledge of networking (L2/L3, load balancing, firewalling, DNS).
• Security practices (secrets management, vulnerability management, hardening).
• Prior SRE/on-call experience with incident response.
• Russian or Lithuanian language skills.

Company offers:

• Collaborative and inclusive team culture.
• Modern office and infrastructure.
• Opportunity to work on critical infrastructure and impactful projects.

Technical expert (Development, Architecture, Teams building) is looking for a right hand. A junior/trainee that wants to get a real projects experience and is ready to learn and tryhard.
 

Ideal Skills:

• Strong organizational / structurizing skills
• VERY Hardworking
• Very good English / presentational skills
• Photo / Video editing
• Positive altitude
• Understanding IT / Development
• +Social media content creation and management
   

What to do = Boost the Projects:

1. Create presentations
2. Manage / organize documentation
3. Create and test the tasks for website functionality
4. Photo / Video editing
5. Manage Social media
6. Find new clients / Organize clients list / send emails

We are seeking an AI QA Engineer with specialization in LLM/NLP model quality assurance to ensure our language models and NLP applications meet the highest standards of accuracy, reliability, and safety. In this role, you will develop rigorous testing strategies for our AI models — including large language models — and lead efforts to detect issues such as factual errors, biases, and instability in model outputs. You will work closely with data scientists and engineers to integrate testing into the model development lifecycle, from early prototyping to post-deployment monitoring. This position is ideal for someone with a strong quality assurance background and a passion for AI, who can bridge the gap between traditional software QA and the unique challenges of evaluating AI systems (chatbots, NLP APIs, etc.) in the context of our Ukrainian LLM project and other products.

What you will do

• Develop and execute comprehensive AI model evaluation strategies to assess the performance of our NLP and LLM systems. Define testing methodologies that cover correctness (e.g., accuracy of responses, compliance with requirements), consistency, and fairness of model outputs.
• Analyze benchmarking datasets, define gaps, and develop the first SOTA benchmarking framework for the Ukrainian language.
• Analyze training datasets and collaborate with data engineers on processing pipelines improvement. Implement a training data testing framework.
• Implement both automated and manual testing for applications powered by large language models. This includes creating automation scripts or test harnesses that can systematically query models with test cases (prompts/questions) and verify responses, as well as performing hands-on review of outputs for subjective evaluation.
• Build and curate high-quality test datasets for model evaluation. Manage a repository of test inputs (e.g., sample user queries, edge-case scenarios, conversational dialogues) along with expected or reference outputs when applicable. Ensure these datasets are diverse, balanced, and representative of real-world use cases, including Ukrainian language content and culturally relevant scenarios.
• Develop pipelines for synthetic data generation and adversarial example creation to challenge the model’s robustness. Use techniques such as paraphrasing, noise injection, or adversarial prompting to produce test cases that can reveal model weaknesses.
• Design and maintain testing frameworks to detect hallucinations, biases, and other failure modes in LLM outputs.
• Define and track key AI performance metrics. Monitor metrics like factual accuracy, coherence/fluency, relevancy to prompt, response diversity, latency of response, and user satisfaction ratings if available. Establish baseline metrics for each new model version and ensure subsequent iterations meet or exceed these benchmarks.
• Work closely with the AI development team to integrate QA in the development process. Collaborate with data scientists to test models at early stages (e.g., evaluating prototypes before full deployment), and with ML engineers to include automated tests in CI/CD pipelines for model updates.
• Debug and analyze AI model failures. When tests uncover issues (e.g., a model consistently gives incorrect information in a certain domain or shows a bias), investigate and identify root causes by analyzing model outputs and underlying data. Provide clear, detailed reports on issues with steps to reproduce and potential causes.
• Provide feedback and recommendations for model improvement. Work with prompt engineers or NLP scientists to refine prompts and instructions that guide the model towards better performance.
• Implement continuous monitoring in production to catch regressions or new issues. Set up mechanisms to regularly evaluate live model outputs (via sampling or user feedback analysis) and alert the team if any quality metrics degrade over time (indicative of model drift or unforeseen use cases).
• Maintain comprehensive test documentation and reports. Document test plans, test case suites, and summarize the results of evaluations for each model version (including graphs/metrics and qualitative findings). Communicate findings to both technical teams and stakeholders in a clear, actionable manner.

Qualifications and experience needed

QA Experience:

• 3+ years in a Quality Assurance or Testing role, with at least part of that focused on testing AI, ML, or complex data-driven systems, and 2+ years in data analysis.
• Strong foundation in QA methodologies, test planning, and test case design.
• Experience writing test plans and handling bug tracking for software projects.

AI/ML Knowledge:

• Familiarity with machine learning concepts and specific challenges of testing AI models.
• Experience with AI/ML testing frameworks and LLM evaluation methodologies — for example, knowledge of how to measure model accuracy on benchmarks, how to perform AB testing on model versions, or using frameworks like Hugging Face’s evaluation tools or custom Python-based testing.

NLP Domain Skills:

• Solid understanding of Natural Language Processing tasks and common failure modes of language models.
• Awareness of issues like model hallucination (making up facts), bias in AI (and methods to test for bias), and the importance of context in language understanding.
• Ideally, hands-on experience testing chatbots, virtual assistants, or language generation systems.

Programming & Tools:

• Proficiency in Python for developing test automation and evaluation scripts.
• Familiarity with testing frameworks (PyTest, unittest) and libraries commonly used in ML/NLP (pandas, numpy for data handling; possibly Hugging Face transformers for model interfacing).
• Experience with tools for dataset handling and annotation; ability to write simple scripts to manipulate and evaluate text data.

Data Management:

• Experience creating and managing test datasets, including annotation and labeling processes.
• Comfortable with basic data engineering to gather logs or outputs from models and analyze them.
• Knowledge of using version control for test scripts and maintaining a repository of test cases.

Analytical Skills:

• Strong problem-solving and debugging skills, specifically applied to AI outputs
• Ability to notice patterns in model errors and analytically determine what they have in common.
• Capacity to interpret model evaluation metrics and translate them into actionable improvements.

Communication:

• Excellent written and verbal communication skills.
• Able to document bugs, write detailed QA reports, and discuss issues with developers and researchers.
• Fluent Ukrainian is a must, as our LLM is oriented towards Ukrainian — you should be able to evaluate outputs in Ukrainian for correctness and nuance.

Attention to Detail:

• A keen eye for spotting subtle errors or oddities in AI behavior.
• Patience and thoroughness in performing manual testing when needed, and creativity in thinking of edge cases or tricky scenarios to test the model’s limits.

A plus would be

AI Testing Tools:

• Experience with specialized tools or frameworks for AI testing, such as model evaluation harnesses, adversarial testing platforms, or crowdsourced evaluation methods.
• Familiarity with techniques like prompt engineering and how prompt changes affect model output quality.

Statistical Analysis:

• Ability to perform statistical analyses on model performance results (significance testing for A/B comparisons, etc.) to determine if changes are improvements.
• Understanding of experiment design in AI (e.g., proper control groups for new model versions).

Continuous Integration:

• Experience integrating tests into CI/CD pipelines for ML — for example, automatically evaluating a model on a validation set every time it’s updated, and blocking deployment if it fails certain criteria.
• Familiarity with ML model versioning and deployment workflows.

Security & Compliance Testing:

• Knowledge of testing AI models for security and compliance issues — e.g., prompt injection attacks on LLMs, data privacy in outputs, or ensuring no disallowed content is generated according to usage policies.

UX Perspective:

• Some experience or understanding of user experience as it relates to AI products.
• Being able to anticipate how end-users might interact with the AI (for instance, phrasing questions in unexpected ways) and ensuring the model handles such interactions gracefully.

Testing Certifications:

• Any certifications or formal training in Quality Assurance, software testing (such as ISTQB) or in AI/ML could be a plus, demonstrating a commitment to the discipline.

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace.
• Remote onboarding.
• Performance bonuses.
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners.
• Health and life insurance.
• Wellbeing program and corporate psychologist.
• Reimbursement of expenses for Kyivstar mobile communication.

Help us push AI further — and faster

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

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

What you’ll do:

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

What you bring:

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

Bonus if you have:

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

About the Data Science Team:

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

What sets us apart:

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

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

About LoopMe:

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

What we offer:

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

Hiring process:

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

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

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

What you will do

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

Qualifications and experience needed

Experience & Background:

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

Cloud & Infrastructure:

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

Containerization & Orchestration:

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

CI/CD & Automation:

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

Programming & Scripting:

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

ML Pipeline Knowledge:

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

Monitoring & Reliability:

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

Security & Compliance:

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

Team Collaboration:

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

A plus would be

LLM/AI Domain Experience:

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

Distributed Computing:

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

Data Engineering Tools:

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

Versioning & Experiment Tracking:

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

Vector Databases & Retrieval:

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

High-Performance Computing:

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

Continuous Learning:

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

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication

Job Description

General:

- Unit Testing: Jasmine, Karma
- E2E Testing: Cypress / Protractor (Cypress preferred)
- Test Coverage & Mocking strategies
- Linting & Formatting: ESLint, Prettier, Stylelint

• Experience testing software systems without user interfaces (i.e. API testing)
• Developing, executing, and maintaining automated test scripts
• Hands-on coding experience with Java 
• Experience with Selenium WebDriver & Jmeter
• Solid understanding of QA practices (black box testing, risk-based testing, system testing, regression testing, exploratory testing)

Must have:
* Test Automation Experience: API (backend) testing (3+ years)
* Test Automation Frameworks: RESTassured, Selenium, Cypress, or Playwright
* Programming Languages: Java (3+ years)
* Tools: Postman, event logging (Splunk/Datadog), CICD pipeline integration
* Regulatory experience
* Excellent English communication skills

Nice to have:
* Salesforce
* Atlassian tools: Jira, Confluence, Bamboo
* mySQL
* Jama QMS

Job Responsibilities

 - Perform testing on software systems without user interfaces, focusing on API testing.
 - Develop, execute, and maintain automated test scripts to ensure software quality and reliability.
 - Write and maintain code using Java or JavaScript.
 - Utilize Python for scripting and automation tasks.
 - Use Selenium WebDriver for web application testing.
 - Implement performance testing using Jmeter.
 - Apply solid QA practices including black box testing, risk-based testing, system testing, regression testing, and exploratory testing to identify and resolve issues.

Department/Project Description

Our client is an innovative manufacturer of medical devices in the United States, producing devices and software applications.

In this project, you will have a great opportunity to be involved in the full development life cycle of medical software, which is designed to assist individuals by processing information from medical devices to identify health trends and track daily activities. In addition, there are opportunities to work with medical devices, in the scope of end-to-end testing.

Here is our dev tech stack:
aws
terraform
bamboo/gitlab
java 11+
Hibernate
Maven
spring/springboot
mysql
okta

Cowchain blockchain development company is actively looking for Backend Developer(Solana) to join our development team.

About us:
Cowchain have successfully completed 120+ projects mainly on EVM-based blockchains such as Ethereum, Polygon, Arbitrum, Base including Coinmarketcap leaders with 180M+ total capitalization and 20M+ daily trading volume in Move2Earn, Play2Earn and DeFi industries.

Required skills:
— At least 3-year commercial experience in the Backend development
— Node.js experience is A MUST
— Ability to use Solscan to analyze data;
— Compiling, signing and sending transfer transactions;
— Compiling, signing and sending swap transactions;
— Transaction mult-signatures
— Pump.fun / Jupiter / Raydium;
— Bignumber.js / bn.js
— Understanding of gas, priority fee, token account creation
— Meme-coin creation Pump.fum/Meteora
— JIRA, gitflow


Tech stack:
— Node.js, Nest.js, Microservices
— MYSQL, MSSQL, PostgreSQL
— TheGraph (Subgraph), Event indexing back-end
— Azure, AWS, Google Cloud
— Docker, Kubernetes

Will be a plus:
— EVM-based blockchains (Ethereum, Avalanche, Polygon, Binance Smart Chain, Velas, Hedera etc)


What will you do:
— new features development
— bugfixes and support existing solutions
— participate in project architecture discussions
— build solutions from scratch as well as join on-going development process
— have fun

What we offer:
— flexible working schedule, remote work
— competitive salary with bonuses for activities
— ability to dive into fast-growing blockchain/crypto industry
— work with modern tech stack (blockchain)
— paid vacations, sick leaves
— 100% friendly/family team

We are looking for a Automation QA Consultant for a 1-3 project.

Responsibilities:

• Automate tests and enhance existing Datamaran E2E Test framework.
• Work closely with developers in the Scrum team members to test new features Manually and automate the tests.
• Mentor testers on Test Automation best practices and industry-standard engineering practices.
• Build and Automate test cases - Collaborate on the design and architecture of the automation framework.
• Stay informed of the latest industry standards and technologies, actively applying these to improve our products.
• Contribute to product discovery phases, bring invaluable insights regarding user-needs and potential solutions.
• Review product specifications and write the test case, develop test plans for assigned areas in the Engineering team for Product features
• Debug and provide needed information for client logged tickets to developers

A one thousand feet view of our tech stack

• For Automation we are using playwright as a framework
• The language being used in the automation framework is javascript
• Our web application is built on node.js, javascript and vue.js 
• Our data stores include MongodB, PostgreSQL and elastic search
• Our server side and data pipelines are built in Python and FastAPI
• Everything is hosted on AWS, on EC2 or in lambda functions

Key Skills/Requirements:

• Over 5 years of professional QA experience across several projects, with a focus on  JavaScript, Playwright .
• Understanding of cross-browser testing
• Experienced building and contributing to an automation framework development
• Must have experience with source control systems like Git.
• Self-driven, detail-oriented, with a strong commitment to quality.
• Excellent communication skills in English, both written and verbal.
• Leadership experience, including the capacity to inspire and motivate team members in a distributed team
• Prior experience working in an agile environment with empowered teams
• Experience in API testing using postman or any other tool like Jmeter.

Bonus points

• Experience in Database especially in PostgreSQL.

Description

Our client is an innovative manufacturer of medical devices in the United States, producing devices and software applications.

In this project, you will have a great opportunity to be involved in the full development life cycle of medical software, which is designed to assist individuals by processing information from medical devices to identify health trends and track daily activities. In addition, there are opportunities to work with medical devices, in the scope of end-to-end testing.

Here is our dev tech stack:
aws
terraform
bamboo/gitlab
java 11+
Hibernate
Maven
spring/springboot
mysql
okta

Requirements

General:

– Unit Testing: Jasmine, Karma
– E2E Testing: Cypress / Protractor (Cypress preferred)
– Test Coverage & Mocking strategies
– Linting & Formatting: ESLint, Prettier, Stylelint

• Experience testing software systems without user interfaces (i.e. API testing)
• Developing, executing, and maintaining automated test scripts
• Hands-on coding experience with Java 
• Experience with Selenium WebDriver & Jmeter
• Solid understanding of QA practices (black box testing, risk-based testing, system testing, regression testing, exploratory testing)

Must have:
* Test Automation Experience: API (backend) testing (3+ years)
* Test Automation Frameworks: RESTassured, Selenium, Cypress, or Playwright
* Programming Languages: Java (3+ years)
* Tools: Postman, event logging (Splunk/Datadog), CICD pipeline integration
* Regulatory experience
* Excellent English communication skills

Nice to have:
* Salesforce
* Atlassian tools: Jira, Confluence, Bamboo
* mySQL
* Jama QMS

Job responsibilities

 – Perform testing on software systems without user interfaces, focusing on API testing.
 – Develop, execute, and maintain automated test scripts to ensure software quality and reliability.
 – Write and maintain code using Java or JavaScript.
 – Utilize Python for scripting and automation tasks.
 – Use Selenium WebDriver for web application testing.
 – Implement performance testing using Jmeter.
 – Apply solid QA practices including black box testing, risk-based testing, system testing, regression testing, and exploratory testing to identify and resolve issues.

Description

Our client is an innovative manufacturer of medical devices in the United States, producing devices and software applications.

In this project, you will have a great opportunity to be involved in the full development life cycle of medical software, which is designed to assist individuals by processing information from medical devices to identify health trends and track daily activities. In addition, there are opportunities to work with medical devices, in the scope of end-to-end testing.

Requirements

• Experience testing software systems without user interfaces (i.e. API testing)
• Developing, executing, and maintaining automated test scripts
• Hands-on coding experience with Java 
• Experience with Selenium WebDriver & Jmeter
• Solid understanding of QA practices (black box testing, risk-based testing, system testing, regression testing, exploratory testing)

Job responsibilities

 – Perform testing on software systems without user interfaces, focusing on API testing.
 – Develop, execute, and maintain automated test scripts to ensure software quality and reliability.
 – Write and maintain code using Java or JavaScript.
 – Utilize Python for scripting and automation tasks.
 – Use Selenium WebDriver for web application testing.
 – Implement performance testing using Jmeter.
 – Apply solid QA practices including black box testing, risk-based testing, system testing, regression testing, and exploratory testing to identify and resolve issues.

Work Modes: Remote (Europe‑friendly time zones) or On‑site with assisted relocation to Iași, Romania or Riga, Latvia.

Employment: Full‑time Relocation (on‑site track): Full package from Ukraine → EU (legal, housing, transport, equipment)

Why join Veido

Veido is a boutique product development house and consulting firm. We empower industries with transformative digital solutions—from mobility and logistics to marketing data. Our products impact over 10,000,000+ users globally. We build fast, ship quality, and work from state‑of‑the‑art offices alongside a supportive team (including many colleagues from Ukraine already on site).

The role

We’re hiring a Middle Go (Golang) Developer to help build next‑generation platforms across transportation/mobility/logistics. You’ll design robust APIs and services, collaborate closely with senior engineers, and contribute to architecture and delivery speed.

What you’ll do

• API development: Design and ship high‑quality back‑end services and API endpoints in Go.
• gRPC & microservices: Implement efficient inter‑service communication (gRPC) within our Google Cloud Platform (GCP) ecosystem.
• Data layer: Work with Cloud Spanner (plus BigQuery exposure is a bonus) for scalable, reliable data access.
• Business analysis: Translate requirements and competitor insights into efficient endpoints and service designs.
• Performance & reliability: Profile hot paths, tune queries, and add observability (metrics/logs/traces) for dependable services.
• Quality & speed: Apply Clean Code principles, write maintainable code, add tests, and continuously improve delivery speed.
• Collaboration: Work closely with the team under guidance from a senior Go developer; participate in code reviews and design sessions.
• Continuous learning: Stay current on Go tooling and cloud best practices; proactively suggest improvements to our stack and workflows.

What you’ll bring

• 2−3+ years of commercial Go experience (exceptional early‑career engineers with strong output are welcome).
• Solid grasp of the Go ecosystem and tooling.
• Hands‑on building HTTP/gRPC APIs; familiarity with distributed systems concepts.
• Experience on GCP; Cloud Spanner experience strongly preferred.
• Clear understanding of system components, data flows, and performance considerations.
• Familiarity with Clean Code practices and modern development workflows (testing, CI/CD, code review).
• Strong problem‑solving skills and effective communication in English (Ukrainian/Russian helpful).
• Bachelor’s in CS or equivalent practical experience.

Nice to have

• Experience with microservices at scale and service observability (OpenTelemetry, Prometheus/Grafana).
• Knowledge of cloud‑based SaaS product development.
• Track record of shipping quickly without sacrificing quality.
• Contributions to open‑source or notable personal projects.

Work modes

Remote (Europe‑friendly):

• Work from anywhere with 4+ hours overlap with EET/EEST.
• Stable connection, security hygiene, and camera‑on collaboration for key sessions.

On‑site with relocation (from Ukraine → EU): This track includes a comprehensive, hands‑on relocation package:

• Legal & residence permits: End‑to‑end guidance; typical onboarding ~1−2 weeks (subject to authorities).
• Housing support: 2−3 months of free accommodation near the office; assistance with deposit and long‑term lease setup.
• Transport & logistics: Flight/ground travel coordination and arrival support.
• Equipment & setup: Day‑1 workstation (laptop/monitor/peripherals) and office access.
• Community: Existing Ukrainian teammates on site to help you settle quickly.

Important: For the on‑site track, applicants must be ready and eligible to relocate to Iași, Romania or Riga, Latvia in compliance with Ukrainian and EU regulations.

Compensation & growth

• Competitive salary (top of market in the region), with increases tied to performance and scope.
• Rapid career growth opportunities in a team that values ownership and mentorship.
• Modern office environment with world‑class amenities and housing within walking distance.

How to apply

• CV/LinkedIn and links to GitHub or notable repos.
• A brief description of your commercial Go experience (projects, stack, your role).
• Your preferred track: Remote or On‑site with Relocation.
• If On‑site: 
  • 1) Preferred location (Iași or Riga), 
  • 2) Earliest relocation date from Ukraine, 
  • 3) Confirmation you are legally able to relocate and work on‑site in the EU.