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fullinfo is a startup B2B data services software company.
We are building an unparalleled data collection pipeline deployed on AWS, written in Go and Typescript. Focused on innovation, quality, and accessibility, we are developing a comprehensive lead generator platform.
The customer-facing part of the solution is a Typescript and GraphQL-based web application, also deployed on AWS. We apply a serverless paradigm:
most of our code runs as AWS Lambdas, with infrastructure managed via Terraform.
We're seeking a Lead Machine Learning Engineer for an initial 12-month B2B contract. You will 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 ML strategy and lead development of scalable, production-grade ML systems on AWS (e.G., Lambda, S3, SageMaker).
* Design robust pipelines to prepare and enrich structured and unstructured data (e.G., JSON, scraped web data) for ML tasks.
* Develop and oversee models for 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 addressing 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 updated on trends in machine learning and AI, identifying 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 (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 workflows and practical deployment (prompt tuning, embeddings, vector search, etc.).
* Familiarity with MLOps practices and tools (e.G., CI/CD, 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, transforming messy data into valuable product features.
* Make architectural decisions and work cross-functionally with product and engineering teams.
* Mentor others and foster a collaborative, high-quality engineering culture.
* Stay curious, solve hard problems, and care about your work's impact on users.
* Balance long-term technical vision with fast, iterative delivery in a startup environment.
What can you expect from us?
* Shape the company from the ground up as a pioneer, helping carve our way forward.
* Collaborate to bring our product to market — celebrate successes together We offer a flat hierarchy and room for innovation in a motivated team.
* Work in a startup environment passionate about quality, problem solving, and building beautiful software.
Our culture is built on two core values:
Quality :
We emphasize quality, building beautiful, reliable software, asking ourselves "Is this right?" and "Does this make sense?".
Problem Solving :
We foster innovation and novel approaches, always keeping user needs at the forefront.
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