Junior AI/ML Engineer, GenAI, AWS

🔥 16 hours ago

🌐 Ukraine, Spain, +3 more countries – Remote

🇺🇦 Ukraine – Remote 🇪🇸 Spain – Remote 🇷🇸 Serbia – Remote 🇦🇲 Armenia – Remote 🇵🇱 Poland – Remote

⏰ Full Time

🟢 Junior

🤖 Machine Learning Engineer

🚫👨‍🎓 No degree required

👻 Ghost score 10%

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Provectus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Provectus is an artificial intelligence consultancy and solutions provider that helps businesses transform through AI. Offering both a use case and a platform approach, Provectus integrates AI into organizations to achieve unique business objectives and technical capabilities. Their solutions are cloud-native, vendor-agnostic, and open, allowing for deployment in customer's cloud without restrictive licenses. With applications in industries like retail, manufacturing, and healthcare, Provectus delivers AI-powered use cases and turnkey solutions to drive innovation and efficiency. They also offer consulting, customization, and managed AI services.

📋 Description

• Build and contribute to RAG system components under senior guidance, with growing autonomy • Write tests and help build evaluation harnesses • Write production code across AI, backend services, and data pipelines with code review support • Integrate AI components into backend services and RESTful APIs • Support deployment of systems to AWS using containers and CI/CD • Contribute to documentation, runbooks, and client handover materials • Participate in technical discussions and architectural decisions • Support model evaluation efforts and investigate and improve failure modes • Take increasing ownership of components and technical decisions • Work in a senior pod alongside an FDE, an FDX, and Senior AI Engineers • Contribute to client delivery work for enterprise AI applications, managed services, and advisory engagements

🎯 Requirements

• Proactive and self-directed; push for clarity rather than waiting for a ticket • Excellent communication and problem-solving skills • Comfortable with some ambiguity, with support from senior team members • B2+ English, comfortable collaborating across distributed, multicultural teams • Hands-on experience building or contributing to RAG systems, ideally in production or near-production • Solid engineering fundamentals; Python and/or TypeScript proficiency • Productive in an unfamiliar codebase with some ramp-up support • Practical AWS experience, such as Lambda, S3, ECS, or similar • Ready to grow into Bedrock and Bedrock AgentCore • Some experience with containers and CI/CD in real projects • Exposure to evaluating non-deterministic systems and test/evaluation cycles • Basic working knowledge of model/agent monitoring concepts • Awareness of cost and latency trade-offs when working with LLMs • Practical experience with LLM APIs, including Anthropic, AWS Bedrock, or OpenAI • 2+ years of software or ML engineering experience, including exposure to production systems • Solid AI/ML foundations and understanding of common model failure modes • Nice to have: financial services, insurance, or healthcare experience • Nice to have: consulting, professional services, or embedded customer-facing delivery • Nice to have: AWS and Claude Code certifications, or actively pursuing them • Nice to have: A2A interoperability concepts • Nice to have: CI/CD pipeline experience, such as GitHub Actions or GitLab CI • Nice to have: NLP, LLM, or recommendation engine experience • Nice to have: Go, TypeScript, or Rust experience • Nice to have: Apache Spark, Apache Airflow, or Kafka experience • Nice to have: Claude Code ecosystem, spec-driven development, or MCP experience

🏖️ Benefits

• Remote-friendly culture • Internal training programs with full support for Claude, AWS, and other professional certifications • Conference attendance • Career growth and active engineer development • Access to the latest AI tools and premium subscriptions • Long-term B2B collaboration • Private medical insurance or a budget for medical needs • Paid sick leave, vacation, and public holidays • Equipment and all the tech needed for comfortable, productive work

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