Mid-Level Machine Learning Engineer

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Full job description

Mid-Level Machine Learning Engineer - Job Description

About Research Grid:

Research Grid (R.grid) are experts in AI-native automation for clinical trials. Our mission is to make trials admin-free, accelerating access to life-saving medicine. We have safely engineered two industry-leading, fully traceable AI products that together form the only end-to-end solution to automate manual back-office workflows from pre-trial planning to trial close.R.grid is a London-based start-up founded in 2020 by Dr Amber Hill. We are a growing team of data scientists, engineers, and business professionals passionate about technology and healthcare.

About the role:

We are looking for a Mid-Level Machine Learning Engineer to support our growing AI initiatives under the guidance of the ML Lead. In this role, you will work within a team of machine learning engineers and data scientists to design, develop, and deploy machine learning solutions that support the company’s broader AI strategy. You will work closely with the ML Lead to translate strategic goals into actionable tasks, oversee the development and deployment of machine learning models, and maintain strong collaboration with cross-functional teams, including software engineering and data science. This role is ideal for someone with solid experience in machine learning development and model deployment, strong problem-solving and organizational skills, and an interest in building scalable solutions using large datasets.

Outline of Role Responsibilities

• Collaborate with the engineering team to make pivotal decisions regarding infrastructure, architecture, and scalability
• Work directly with the ML Lead as well as the Tech Lead, CTO, and product team to incorporate their aims with the machine learning strategy and development
• Communicate deep scientific concepts in understandable language for internal teams and clients
• Create systems that benchmark advancement, prevent regressions, and are simple to manage while embracing the challenges of big data, performance, and scalability
• Evaluate intelligent insights from data and create compelling visualizations and reports
• Explore techniques to enhance pretraining and alignment data
• Ensure data quality and integrity, testing, and attention to detail for high-quality engineering
• Develop data mining and collection algorithms to enrich and augment customer data with outside-world knowledge
• Build ownership of all ML pipelines within the products, working toward their continuous improvement
• Build on and expand in-house NLP / OCR / LLM algorithms, analytic systems, and predictive models
• Maintain and scale existing technology stack with the ML Lead and Tech Lead.
• Stay informed of the latest data science, health tech, and machine learning developments.
• Keep to industry regulatory requirements and standards (e.g., comment code, C4 diagrams, CSV upkeep, security standards, etc.)
• Manage time effectively and work progressively toward the Company goals

Essential qualifications, experience, knowledge, and skills:

• 3 - 5 years of total Machine learning experience and currently in a Lead NLP / OCR / LLM Engineer, Lead Data Scientist, or Lead / Senior Machine Learning Engineer role
• Excellent knowledge of Python and the R language.
• Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or JAX
• Solid understanding of natural language processing, computer vision, and neural networks
• Knowledge of data management and visualization techniques
• Expertise in statistical analysis and predictive modeling
• Good knowledge of ML systems with search or retrieval systems (Elasticsearch / OpenSearch).
• Extensive knowledge of machine learning frameworks and libraries (e.g., scikit-learn)
• Strong problem-solving abilities and critical thinking skills.
• Great attention to detail.
• Excellent communication and collaboration skills.
• Excellent organizational skills, with the ability to work on multiple projects at the same time
• Self-motivated with a good work ethic and time management skills.
• Experience with scaling ML solutions to the commercial level is a must-have.
• Experience deploying ML models using Docker, REST APIs, or batch pipelines.
• Experience with LLM pipelines (RAG, embeddings, vector databases).
• Familiarity with MLOps practices (model versioning, experiment tracking, monitoring)
• Hands-on experience with cloud platforms (preferably AWS: S3, Lambda, EC2, SageMaker) is a plus.

Desirable qualifications, experience, knowledge, and skills:

• Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
• Experience in a start-up company
• Experience and familiarity in an applied STEM company
• Experience with big data technologies (e.g., Hadoop, Spark).
• Experience with Patent works

Job Types: Full-time, Permanent

Pay: £55,000.00-£65,000.00 per year

Benefits:

• Company pension
• Work from home

Work Location: Hybrid remote in London N1 9AB