Tech Lead – Machine Learning

Softvil Technologies Pvt Ltd

Singapore

On-site

SGD 120,000 - 150,000

Full time

14 days+
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Job summary

A leading technology firm is seeking a Tech Lead – Machine Learning in Singapore. The ideal candidate will have over 10 years of experience in the field, with significant leadership experience in machine learning projects. Responsibilities include designing scalable ML systems, mentoring engineers, and collaborating with business stakeholders to deliver AI solutions in the banking and financial services sector. The role requires proficiency in multiple programming languages and ML frameworks, alongside strong project management skills.

Qualifications

  • 10+ years of professional experience with at least 5 in a hands-on data/ML role.
  • Prior experience in leadership positions in ML.
  • Strong analytical thinking and attention to detail.

Responsibilities

  • Design scalable, production-ready ML systems.
  • Guide ML engineers and data scientists through code reviews.
  • Lead end-to-end development lifecycle of ML models.
  • Collaborate with stakeholders to translate goals into ML solutions.

Skills

Proficiency in Python
ML frameworks expertise (TensorFlow, PyTorch)
Cloud platforms (AWS, Azure, GCP)
Data engineering (Spark, SQL)
DevOps tools (Docker, Kubernetes)

Education

Bachelor’s degree in Computer Science or related discipline

Tools

MLflow
Kubeflow
SageMaker
Airflow

Job description

Tech Lead – Machine Learning (Fixed Term Contract)

Are you passionate about leading AI and Machine Learning initiatives at scale? We’re looking for a Tech Lead – Machine Learning (ML) to drive our data science and AI programs, shaping innovative solutions in the banking and financial services sector. As part of our advanced technology team, you’ll lead the design and deployment of scalable ML systems, mentor a team of ML engineers and data scientists, and ensure the highest engineering standards across projects.

Key Responsibilities
  • Design scalable, production‑ready machine learning systems that align with business and technical requirements.
  • Guide and support ML engineers and data scientists through code reviews, knowledge sharing, and technical direction.
  • Lead the end‑to‑end development lifecycle of ML models—including data preprocessing, training, evaluation, deployment, and performance monitoring.
  • Maintain robust standards in code quality, testing, documentation, version control, and reproducibility of ML experiments and pipelines.
  • Collaborate with product and business stakeholders to translate strategic goals into eƯective AI/ML solutions.
  • Estimate eƯort, manage project timelines, and ensure successful delivery of ML features in line with enterprise goals.
Qualifications
  • Bachelor’s degree in Computer Science, Information Technology, or a related discipline.
  • 10+ years of professional experience, including at least 5 years in a hands‑on data/ML role.
  • Proficiency in programming languages (Python, Scala, Java), ML/AI frameworks (TensorFlow, PyTorch, Scikit‑learn), MLOps tools (MLflow, Kubeflow, SageMaker, Airflow), cloud platforms (AWS, Azure, GCP), data engineering (Spark, Kafka, SQL, Snowflake), DevOps tools (Docker, Kubernetes, Terraform), and model governance techniques including model cards and explainability tools.
  • Prior experience in roles such as Tech Lead – ML, Senior Tech Lead – ML, or equivalent leadership positions.
  • Exposure to the financial services domain is a strong advantage.
  • Demonstrated experience in modernizing IT systems and working on large‑scale enterprise applications.
  • Strong attention to detail and analytical thinking.
  • Curiosity and adaptability in learning new tools and domains.
  • Ability to work independently and thrive in a collaborative team culture.
  • Alignment with ComBank’s organizational values and technology culture.
  • Proven ability to mentor and lead diverse technical teams.
  • Project management skills including task estimation, timeline planning, and stakeholder communication.
  • EƯective in translating complex technical concepts into actionable business solutions.
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