Senior Machine Learning Engineer

Qodea; Greater London; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

Competitive base salary

Matching pension scheme

Private medical insurance

36 days annual leave

Flexible working hours

Work from anywhere (up to 3 weeks per year)

Job summary

An innovative IT firm in Greater London is seeking a Senior Machine Learning Engineer to manage the full lifecycle of machine learning models. Your role will include designing, building, and deploying ML solutions that enhance user experience. You will lead algorithm design, conduct data analysis, and mentor team members. Ideal candidates have extensive experience in ML systems, programming in Python, and using frameworks like TensorFlow and PyTorch. Join a company that values diversity and offers a competitive salary and benefits.

Qualifications

• Hands-on experience designing and deploying production-grade machine learning systems.
• Strong foundational knowledge of various machine learning algorithms.
• Proven ability in recommendation systems and NLP.

Responsibilities

• Lead the selection and design of machine learning models.
• Implement model observability and optimization processes.
• Collaborate with teams to deliver AI-driven solutions.

Skills

Machine Learning

Python

Data Analysis

NLP

Data Processing with Spark

Tools

Pandas

Scikit-learn

TensorFlow

PyTorch

SQL

GCP

Job description

About the Role

We are looking for a Senior Machine Learning Engineer responsible for the end-to-end lifecycle of machine learning models that power core product features. You will design, build, and deploy innovative ML solutions that directly impact the user experience through personalization, recommendations, and intelligent systems.

Responsibilities

• Lead the algorithm selection, design, and prototyping of machine learning models to solve complex business problems, including recommendation, personalization, and predictive analytics.
• Apply expertise in statistical modeling and machine learning to perform deep data analysis, guide crucial feature selection, and identify opportunities for product improvement.
• Own the full ML lifecycle, from breaking down discrete steps of a pipeline (e.g., with a DAG) to analyzing model implementations and improving their robustness in the wild.
• Implement and manage robust model observability, tuning, and optimization processes to ensure sustained performance and accuracy post-deployment.
• Develop and maintain data pipelines to process and prepare data for model training and evaluation.
• Design and conduct A/B tests to evaluate model performance and its impact on key business metrics.
• Collaborate closely with product managers and engineers to define problems and deliver effective AI-driven solutions.
• Mentor other team members, champion best practices in machine learning engineering, and stay current with the latest advancements in the field.

Requirements

• Hands‑on experience designing and deploying production‑grade machine learning systems.
• Strong foundational knowledge of various machine learning algorithms and a proven ability to select the appropriate methodology, avoiding a one‑size‑fits‑all approach.
• Proven experience in areas such as recommendation systems, personalization, natural language processing (NLP), or semantic search.
• Expert‑level programming skills in Python, with deep, hands‑on experience using data science and ML libraries such as Pandas, Scikit‑learn, TensorFlow, or PyTorch.
• Experience with data storage technologies (e.g., SQL, NoSQL, key‑value) and their scaling characteristics.
• Experience with large‑scale data processing technologies (e.g., Spark, Beam, Flink) and associated patterns (batch vs. stream), with a deep understanding of when to use them.
• Experience using cloud platforms (e.g., GCP) at scale.
• Experience deploying ML‑based solutions at scale using cloud‑native services.
• Excellent communication and collaboration skills, with the ability to thrive in a fast‑paced, cross‑functional team environment.

Benefits

• Competitive base salary
• Matching pension scheme (up to 5%) from day one
• Discretionary company bonus scheme
• 4× annual salary death‑in‑service coverage from day one
• Employee referral scheme
• Tech scheme
• Private medical insurance from day one
• Optical and dental cashback scheme
• Help@Hand app: access to remote GPs, second opinions, mental health support, and physiotherapy
• EAP service
• Cycle‑to‑work scheme
• 36 days annual leave (inclusive of bank holidays)
• One paid day off for your birthday
• Ten paid learning days per year
• Flexible working hours
• Market‑leading parental leave
• Sabbatical leave (after five years)
• Work from anywhere (up to 3 weeks per year)
• Industry‑recognised training and certifications
• Bonusly employee recognition and rewards platform
• Clear opportunities for career development
• Length of service awards
• Regular company events

Diversity and Inclusion

At Qodea, we champion diversity and inclusion. We believe that a career in IT should be open to everyone, regardless of race, ethnicity, gender, age, sexual orientation, disability, or neurotype. We value the unique talents and perspectives that each individual brings to our team, and we strive to create a fair and accessible hiring process for all.

Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Information Technology

Industries

IT Services and IT Consulting