Machine Learning Engineer II

Zonda; Glasgow; On-site; GBP 45,000 - 65,000; Full time

Job summary

A dynamic technology company in Glasgow is seeking a mid-level ML Engineer (Natural Language Processing) II to work on the development and maintenance of LLM-based products. The ideal candidate should have significant experience with machine learning and a strong proficiency in Python. Responsibilities include deploying NLP models and collaborating with various teams. An excellent opportunity for career growth awaits with a supportive environment offering competitive benefits.

Benefits

Paid vacation and general holidays

Employee & Family Assistance Program (EFAP)

Qualifications

• 3+ years of experience in Machine Learning, Data Science, or a related field.
• Experience with retrieval systems, embeddings, and vector DBs like Weaviate or Pinecone.
• Strong mathematical, analytical, and problem-solving skills.

Responsibilities

• Develop, optimise, and deploy NLP/LLM models.
• Collaborate with Product Managers, software engineering teams, and other departments to design NLP products.
• Monitor ML models in production and establish corrective measures for restoring model performance.

Skills

Software programming

Mathematics

DevOps

Good communication skills

Education

Bachelor's degree in computer science, Engineering, or a related field

Tools

Python

PyTorch

scikit-learn

AWS

Google Cloud

Azure

Docker

Kubernetes

Git

Job description

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The ML Engineer (Natural Language Processing) II is a mid-level position responsible forNatural Language models-based product development and maintenance. As a mid-levelengineer in this role, you will work closely with senior engineers and non-technical businessstake holders, contributing to the entire lifecycle of building and maintaining emergingLLM/NLP-based ML products. An important aspect of this role would be product design andexecution bearing cost efficiency and speed. The ideal candidate would have skills in softwareprogramming, ML, agentic workflows, mathematics, and DevOps. Good communication skillswith an ability to demystify ML algorithms and capabilities is a must, as stakeholders in MLproducts include software engineering teams as well as non-technical business partners.

What You'll Do

• Curation, cleaning, and maintenance of datasets for NLP/LLM models.
• Develop, optimise, and deploy NLP/LLM models.
• Work with agentic frameworks like LangChain, CrewAI, or AutoGen to develop multi[1]step agents or workflows
• Work with Product stakeholders to capture and establish requirements for naturallanguage models-based products.
• Collaborate with Product Managers, software engineering teams, and otherdepartments to design NLP products for inference.
• Steer consolidation of dataset requirements, acquiring data, annotation,management, and version control for NLP applications.
• Monitor ML models in production, setting metrics to identify drift, and establishcorrective measures for restoring model performance.
• Identify and implement appropriate tools for monitoring product performance ininference.
• Ownership of technical documentation related to datasets, model selection, trainingexperiments, and production infrastructure.
• Continual learning and self-improvement with a focus on latest trends, techniques,and best practices in Machine Learning.

Who You Are

• Bachelor's degree in computer science, Engineering, or a related field.
• 3+ years of experience in Machine Learning, Data Science, or a related field.
• Proficient in Python and working knowledge of ML libraries PyTorch and scikit-learn.
• You’ve built and deployed at least one LLM-based or NLP-heavy product in a realsetting likely using agentic frameworks like LangGraph, LangChain, AutoGen etc.
• Strong mathematical, analytical, and problem-solving skills.
• Experience with retrieval systems, embeddings, and vector DBs like Weaviate orPinecone.
• Good understanding of Machine Learning algorithms and models (Languageprocessing models such as GPT, BERT, etc).
• Experience in designing ML products for inference in cloud.
• Ability to structure and execute an ML project from start to completion, for bothtraining and inference.
• Excellent communication and teamwork skills; ability to work in a team.
• Experience with cloud computing platforms like AWS, Google Cloud, or Azure.
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems like Git.

Nice to have.

• Masters in a specific field such as Statistics, Data Science, Machine Learning, or AI.
• Utilization of Generative AI models.
• Knowledge of SQL and NoSQL databases including construction of queries, queryoptimization, and schema design.
• API development using standard tools such as FastAPI or Flask

Administrative

• The candidate must have the right to work in UK

Why People Love Working Here

• We offer meaningful work and opportunities for career growth
• Paid vacation and general holidays
• Employee & Family Assistance Program (EFAP)