ABOUT RESEARCH GRID:

Research Grid (R.grid) is the automation engine for admin-free clinical trials. Our mission is to enable faster, more successful clinical trials by engineering smart software that safely automates back-office admin across the full lifecycle. R.grid has developed two industry-leading products leveraging its AI-powered automation engine. Together, Inclusive and TrialEngine form the only end-to-end platform to automate the back office of clinical trials, from pre-trial to trial close. R.grid is London-based start-up founded in 2020 by Dr Amber Hill. We are a small but growing team of data scientists, engineers, and business professionals passionate about technology and healthcare.

ESSENTIAL QUALIFICATIONS, EXPERIENCE, KNOWLEDGE, AND SKILLS:

• 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 R language.
• Atleast 2 Years of ML-Ops experience.
• Familiarity with deep learning frameworks such as TensorFlow, Py Torch, 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 ElasticSearch Python, R, elastic search queries, and AWS lambda functions
• Extensive knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, sci-kit-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
• Demonstrated leadership experience, with a track record of managing and mentoring technical teams

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) and cloud platforms (e.g., AWS, Google Cloud).
• Experience with CI/CD, AWS Elastic Beanstalk, AWS Lambda, and Elastic Search
• Experience with Patent works
  Job Types: Full-time, Permanent
  Pay: £60,000.00-£70,000.00 per year

Benefits:

• Company pension
• Sick pay
• UK visa sponsorship
• Work from home

Schedule:

• Monday to Friday

Education:

• Master’s (required)

Experience:

• AWS: 1 year (preferred)
• MLOps: 2 years (preferred)
• Python: 5 years (required)
• NLP: 5 years (preferred)
• LLMs: 3 years (preferred)
• OCR: 2 years (preferred)

Language:

• English (required)

Work authorisation:

• United Kingdom (preferred)

Reference ID: ml-manager-rgri

ABOUT THE ROLE:

We are looking for a Machine Learning Manager who can lead our Machine Learning team and execution of our long-term ML strategy. As the Machine Learning Manager, you will play a pivotal role in shaping our AI strategy and leading a team of talented machine learning engineers and data scientists. You will be responsible for overseeing the development and implementation of machine learning models, ensuring they meet the highest standards of performance and reliability. Your expertise will drive the creation of innovative solutions that address complex business challenges and enhance our competitive edge. In this role, you will experiment with, build, and expand NLP, OCR, and LLM algorithms, as well as analytic systems and other predictive models. You will lead a machine learning team and collaborate closely with software engineers and data scientists. Responsibilities will include overseeing data mining and collection procedures, ensuring data quality and integrity, visualizing data, creating reports, and aligning data projects with organizational goals. As a perfect candidate, you should have a strong problem-solving ability and a background in mathematical modeling and statistical analysis.

OUTLINE OF ROLE RESPONSIBILITIES

• Lead and manage a team of machine learning engineers and data processing associates
• Collaborate with the engineering team to make pivotal decisions regarding infrastructure, architecture, and scalability
• Work directly with the CTO as well as the CEO, COO, and product team to incorporate their aims with the machine learning strategy and development
• Support CTO with ad-hoc and strategic tasks
• 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 (including ML-Ops) within the products, working toward their continuous improvement
• Build on and expand in-house NLP / OCR / LLM algorithms, analytic systems, and predictive models
• Create, plan, and prioritize ML roadmaps based on and aligned with company goals
• Maintain and scale existing technology stack.
• 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 Company goals