Signify Technology
Machine Learning Engineer – Signify Technology
We’re looking for a Machine Learning Engineer to join a fast-growing, data‑driven team working on cutting‑edge ML solutions. This role is ideal for someone hands‑on with ML models and MLOps who is keen to grow into a senior‑level position in the near future.
You’ll be involved end‑to‑end — from building and deploying models to improving scalability, monitoring, and production readiness. There’s also strong scope for technical leadership, mentorship, and ownership as the team grows.
What You’ll Be Doing
Design, build, train, and deploy ML and deep learning models into production
Work closely with data and engineering teams on model deployment, monitoring, and optimisation
Implement and maintain MLOps pipelines, CI/CD workflows, and model lifecycle management
Contribute to work involving LLMs, including fine‑tuning, optimisation, and evaluation
Own and explain the models you build — what you built, why, and how they perform
Mentor junior engineers and contribute to technical decision‑making as the team scales
Core Requirements
Strong experience building ML and deep learning models
Excellent Python skills (SQL and PySpark are a plus)
Hands‑on experience with MLOps, CI/CD pipelines, model deployment, and monitoring
Experience using ML frameworks such as PyTorch (or Keras), Scikit‑learn, and Pandas
Strong problem‑solving mindset with a proactive, ownership‑driven approach
Comfortable working independently and collaboratively
Excellent communication skills in English
Nice to Have / Preferred
Experience working with Large Language Models (LLMs)
Knowledge of efficient ML techniques (quantization, distillation, transfer learning, fine‑tuning)
Experience with Azure services, including Azure Data Lake / Datahouse and Azure Databricks
Exposure to REST APIs
Familiarity with Docker and Kubernetes
Any experience in people leadership, mentorship, or team guidance (highly valued)
Seniority level
Mid‑Senior level
Employment type
Contract
Job function
Software Development
Referrals increase your chances of interviewing at Signify Technology by 2x
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You’ll be involved end‑to‑end — from building and deploying models to improving scalability, monitoring, and production readiness. There’s also strong scope for technical leadership, mentorship, and ownership as the team grows.
What You’ll Be Doing
Design, build, train, and deploy ML and deep learning models into production
Work closely with data and engineering teams on model deployment, monitoring, and optimisation
Implement and maintain MLOps pipelines, CI/CD workflows, and model lifecycle management
Contribute to work involving LLMs, including fine‑tuning, optimisation, and evaluation
Own and explain the models you build — what you built, why, and how they perform
Mentor junior engineers and contribute to technical decision‑making as the team scales
Core Requirements
Strong experience building ML and deep learning models
Excellent Python skills (SQL and PySpark are a plus)
Hands‑on experience with MLOps, CI/CD pipelines, model deployment, and monitoring
Experience using ML frameworks such as PyTorch (or Keras), Scikit‑learn, and Pandas
Strong problem‑solving mindset with a proactive, ownership‑driven approach
Comfortable working independently and collaboratively
Excellent communication skills in English
Nice to Have / Preferred
Experience working with Large Language Models (LLMs)
Knowledge of efficient ML techniques (quantization, distillation, transfer learning, fine‑tuning)
Experience with Azure services, including Azure Data Lake / Datahouse and Azure Databricks
Exposure to REST APIs
Familiarity with Docker and Kubernetes
Any experience in people leadership, mentorship, or team guidance (highly valued)
Seniority level
Mid‑Senior level
Employment type
Contract
Job function
Software Development
Referrals increase your chances of interviewing at Signify Technology by 2x
#J-18808-Ljbffr