AI/ML Engineer

TALENTSIS PTE. LTD.; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

TALENTSIS PTE. LTD. is seeking a data-driven ML Engineer to perform exploratory data analysis and translate business problems into AI solutions. You will design, train, and optimise models, deploy them to production, and collaborate with software engineering and DevOps teams.

Ideal candidates have 3+ years of hands-on ML experience, proficiency in Python and SQL, and familiarity with TensorFlow or PyTorch. Knowledge of APIs, Kubernetes, and Docker is a plus. East/West Singapore location.

Qualifications

• 3+ years hands-on ML implementation, deployment, and analytics on large datasets.
• Translate business problems into analytical ML solutions.
• Proficient in Python, SQL, data wrangling and data visualisation.
• Experience deploying models to production and APIs.

Responsibilities

• Perform exploratory data analysis (EDA) to uncover trends and insights from large datasets.
• Translate business problems into analytical and machine learning solutions.
• Design, develop, train, and optimise machine learning models and algorithms.
• Evaluate model performance using validation techniques and hyperparameter tuning.
• Deploy models into production environments and integrate with applications via APIs.
• Collaborate with software engineering and DevOps to build scalable AI solutions.
• Monitor deployed models and improve accuracy and efficiency.
• Present findings to technical and non-technical stakeholders.
• Stay current with AI/ML advancements and best practices.

Skills

Python

SQL

Data Wrangling

Data Visualisation

DBMS

Tools

TensorFlow

PyTorch

Qlik Sense

Kubernetes

Docker

Job description

Key Responsibilities:

• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from large datasets.
• Translate business problems into analytical and machine learning solutions.
• Design, develop, train, and optimise machine learning models and algorithms.
• Evaluate model performance using appropriate validation techniques, hyperparameter tuning, and model optimisation methods.
• Deploy machine learning models into production environments and integrate them with existing applications through APIs.
• Collaborate with software engineering and DevOps teams to build scalable, production-ready AI solutions.
• Monitor deployed models, troubleshoot issues, and continuously improve model accuracy and efficiency.
• Present analytical findings and recommendations clearly to both technical and non-technical stakeholders.
• Stay current with advancements in AI, machine learning, and data science, recommending new tools and best practices where applicable.

Requirements:

• Minimum 3 years of hands-on experience in machine learning implementation, deployment, and statistical data analysis involving large datasets.
• Strong experience translating business requirements into analytical solutions using statistical and machine learning techniques.
• Proficient in:PythonSQLData WranglingData VisualisationDatabase Management Systems (DBMS)
• Experience with one or more of the following:TensorFlowPyTorchRSASQlik Sense
• Experience deploying machine learning models into production environments.
• Familiarity with Agile development methodologies such as Scrum is preferred.

Nice to Have:

Experience with any of the following technologies would be advantageous:

• Power BI
• Microsoft Access
• SharePoint
• Kubernetes
• Docker or Podman
• Microservices Architecture
• DevSecOps practices

Work Location: East / West

Only shortlisted candidates will be notified.

(EA Reg No: 20C0312)