AI/ML Engineer

AI/ML ENGINEER Would you like to be a part of Recordly's story? Now is your chance! We’re looking for Senior AI/ML Engineers who want to get their hands dirty building modern AI, ML, and GenAI solutions in production environments. Working at Recordly means you get to work with customers that truly want to make data and AI/ML their competitive edge. You will be at the core of helping businesses capitalize on the opportunities data offers. As an AI/ML Engineer, you’ll work hands-on with real customer solutions, building AI and machine learning pipelines in different data environments. Over time, as your skills and experience grow, your role can evolve toward more senior responsibilities within our career framework. "WHO/WHAT IS RECORDLY?" YOU MIGHT ASK At Recordly, we believe data and AI are transforming the way businesses create value. While this transformation is already reshaping industries, many organizations are still searching for practical ways to realize its full potential. Our experienced data professionals help companies bridge that gap, turning data and AI into meaningful business outcomes. Our mission is to define how humans and data co-operate. We want to support businesses in understanding the data they already have, the opportunities they’re not yet capturing, and how to use these to enhance strategic KPIs. Simultaneously, we aim to translate business requirements into actionable tasks for teams working with the data or related technologies. We work closely with our customers to make this happen. Our expertise covers data engineering, data architectures, and data management as well as hands-on AI and ML solutions, GenAI applications, and agentic systems. Whether it’s real-time pipelines, enterprise ML platforms, or modern cloud ecosystems, we focus on solutions that are practical, scalable, and built for long-term value. We're tech-agnostic, but some of our most commonly used tools include Azure, GCP, AWS, Snowflake, dbt, and Databricks. In simple terms: we tech the heck out of data. What sets us apart is who we are and how we do it. Our employee promise (besides offering engaging customer assignments, of course) includes the possibility of enjoying the company's success and shaping who we are and what we do together. We believe in being open about how the business is going and how our choices affect the bottom line. Take a look at our site to get to know us better! WHAT WE’RE LOOKING FOR As an AI/ML Engineer at Recordly, you build AI and machine learning solutions that work in real production environments, not just as prototypes. Hands-on work is the norm: one day you're designing a agentic solution architecture on top of a customer's proprietary data, the next you're building an evaluation suite together with end users, and the day after that you're writing data pipelines when the Data Engineers aren't around. Your background can be in machine learning, software engineering, or already on the GenAI side; what matters is that you care about both how models work and how to get them reliably into production. We hope you have a few years of relevant experience. Technical requirements Core expectations (you don’t need to tick every box, but most should feel familiar): Strong Python skills as it's our main development tool; experience with other languages is a plus Hands-on experience with generative AI: RAG architectures, embeddings, vector databases, prompt engineering, and at least one orchestration framework (LlamaIndex, LangGraph, Langchain or similar) Hands-on experience designing and delivering ML solutions in production: supervised/unsupervised models, feature engineering, training pipelines, and model deployment across the full lifecycle Understanding of agentic systems: tool use, multi-step planning, skills, MCP and a healthy sense of when not to reach for an agent MLOps fundamentals: model pipelines, versioning, monitoring, and observability of LLM applications in production Ability to translate business requirements into technical solutions and communicate them clearly to different stakeholders Experience with at least one cloud environment (Azure, AWS, or GCP) and its AI/ML services Solid fundamentals in containerisation (Docker) and CI/CD practices. Nice to have: Experience building evaluation frameworks: faithfulness, correctness, relevance; we treat evals as code Awareness of responsible AI: data privacy, prompt injection defences, output guardrails, and the EU AI Act Experience with traditional ML models and their production use (scikit-learn, PyTorch, TensorFlow, or similar) Solid SQL skills for exploring data, shaping it for retrieval, and integrating with structured sources Full stack development experience (We are building increasing number of agentic applications with UI) Willingness to pick up unfamiliar tech; a lot of the work these days involves spinning up something you've never touched before and making it work. What we're especially looking for right now: Designing and i