Would you like to partake in technical challenges, collaborate on an interesting product, be up to date with the latest technology, and contribute to taking our product to market? Then keep reading
Yes, tell me more…
fullinfo is a startup B2B data services software company.
We are building an un-paralleled data collection pipeline which is being deployed on AWS and written in Go and Typescript. With a focus on innovation, quality, and accessibility, we are developing a one-stop lead generator platform.
The Customer facing part of the solution is a Typescript and GraphQL based web application. Deployed on AWS as well. Serverless paradigm is being applied: Most of our code is running as AWS's Lambda's. AWS infrastructure is managed by applying Terraform.
We're looking for a Lead Machine Learning Engineer to join on an initial 12-month B2B contract basis. In this role, you'll drive the strategy and execution of ML systems that power our product, from ideation to deployment. You'll collaborate across teams, mentor others, and ensure our ML efforts are scalable, impactful, and aligned with business goals.
Responsibilities:
* Define the ML strategy and lead the development of scalable, production-grade machine learning systems on AWS (e.g., Lambda, S3, SageMaker).
* Guide the design of robust pipelines to prepare and enrich structured and unstructured data (e.g., JSON, scraped web data) for ML tasks.
* Develop and oversee models for tasks such as data classification, entity resolution, relationship detection, and summarization.
* Lead experimentation with LLMs (e.g., GPT, BERT, LLaMA), including prompt engineering, embedding generation, fine-tuning, and RAG approaches.
* Collaborate with product, engineering, and data teams to integrate ML into product features that solve real customer problems.
* Establish and maintain best practices for model evaluation, monitoring, observability, and reproducibility.
* Mentor ML engineers and help shape a high-performance, learning-oriented ML team.
* Stay ahead of trends in machine learning and AI, and identify opportunities to apply emerging techniques within our product.
Requirements:
* Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.
* 6+ years of hands-on experience in applied machine learning, with at least 1–2 years in a technical leadership or lead role.
* Strong Python skills and fluency with ML/NLP libraries and frameworks (e.g., Pandas, scikit-learn, Hugging Face, PyTorch, boto3).
* Proven experience deploying ML systems on AWS (e.g., SageMaker, Lambda, ECS).
* Experience working with semi-structured and unstructured data at scale (e.g., NoSQL, web data, nested JSON).
* Deep understanding of LLM-based workflows and practical deployment (prompt tuning, embeddings, vector search, etc.).
* Familiarity with MLOps practices and tools (e.g., CI/CD for ML, monitoring, versioning).
* Experience with infrastructure-as-code tools like Terraform is a plus.
* Excellent communication and collaboration skills. Business-level English required.
The successful candidate will…
* Take ownership of ML initiatives end-to-end and enjoy turning real-world messy data into valuable product features.
* Are comfortable making architectural decisions and working cross-functionally with product and engineering teams.
* Enjoy mentoring others and fostering a collaborative, high-quality engineering culture.
* Stay curious, love solving hard problems, and care deeply about how your work impacts the user.
* Appreciate the balance between long-term technical vision and fast, iterative delivery in a startup environment.
What can you expect from us?
* To shape the company from the ground up – join our team as a pioneer and help us carve our way forward.
* Together we'll take our product to market – how cool would it be to celebrate together?A flat hierarchical structure with room for innovation in a highly motivated team.
* A start-up environment that is passionate about quality, problem solving and building beautiful software.
Our passion stems from our shared values and mission. With that said, our culture is built on two major aspects:
Quality: At fullinfo we have show-and-tell energy, and we let the quality of our product speak for itself. We love building beautiful software and get hyped by always raising the bar on quality. Our product is beautiful inside and outside. How do we achieve this? By always asking ourselves "Is this right?" or "Does this make sense?".
Problem Solving: We foster innovation and novel approaches to problem solving, while keeping user needs at front of mind.