Endava Technology

1 day ago

Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Design and build secure, scalable AI/ML platforms that take models from experimentation to production. Own end-to-end ML/AI lifecycle workflows including data validation, training, evaluation, deployment, monitoring, and drift handling. Build cloud foundations with Terraform, engineer production services using Python and APIs, and automate delivery with CI/CD and environment-promotion practices. Work with Docker/Kubernetes and modern MLOps tooling, including Vertex AI where relevant, to ensure reliable operations.

Location: Singapore

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Translate business and data challenges into scalable, secure, observable solution architectures and communicate trade-offs for client delivery teams.
•Design and provision cloud foundations using Terraform, applying networking, identity, security, secrets management, and cost-management practices.
•Engineer production systems by writing clean, tested, maintainable Python code, automation scripts, and building data/ML services, APIs, and workloads.
•Automate delivery and operations with CI/CD and CI/CT pipelines, covering versioning, testing, packaging, deployment, rollback, and environment promotion.
•Own the ML and AI lifecycle with repeatable workflows for validation, experimentation, training, evaluation, deployment, monitoring, drift detection, and incident response; build/evaluate LLM, RAG, and agentic capabilities when relevant.

Pay and Benefits

Equity and Bonus:Equity

Perks:Employee Assistance

Key Requirements

•Hands-on experience taking data science or machine learning work from exploration through deployment and ongoing production operation.
•Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Data Science, AI, or a related quantitative field (or equivalent practical experience).
•Strong Python development skills for tested, maintainable production code, APIs, automation, and operational scripts, with Git-based development and code review practices.
•Practical ML experience with libraries such as Scikit-learn, TensorFlow, and/or PyTorch, including model development, evaluation, and core algorithm concepts.
•Hands-on MLOps and platform engineering experience with Docker and Kubernetes (or managed containers), plus Terraform/infrastructure-as-code and major cloud exposure (GCP preferred).

Education:Bachelor's

Skills:Engineering rigorProblem-solvingConsulting mindsetCommunicationCreative problem-solving

Languages:English

Tech Stack:PythonAPIsGitGitHub ActionsGitLab CIAzure DevOpsCloud BuildTerraformTerraform modulesSQLPandasNumPyScikit-learnTensorFlowPyTorchDockerKubernetesHelmArgo CDMLflow

Company Brief

Endava Technology

Provides IT services and digital engineering, delivering software development, automation, and consulting to enterprises across financial services, payments, telecommunications, and retail to accelerate digital transformation.

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Website LinkedIn

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Endava Technology

1 day ago

Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Translate business and data challenges into scalable, secure, observable solution architectures and communicate trade-offs for client delivery teams.
•Design and provision cloud foundations using Terraform, applying networking, identity, security, secrets management, and cost-management practices.
•Engineer production systems by writing clean, tested, maintainable Python code, automation scripts, and building data/ML services, APIs, and workloads.
•Automate delivery and operations with CI/CD and CI/CT pipelines, covering versioning, testing, packaging, deployment, rollback, and environment promotion.
•Own the ML and AI lifecycle with repeatable workflows for validation, experimentation, training, evaluation, deployment, monitoring, drift detection, and incident response; build/evaluate LLM, RAG, and agentic capabilities when relevant.

Pay and Benefits

Equity and Bonus:Equity

Perks:Employee Assistance

Key Requirements

•Hands-on experience taking data science or machine learning work from exploration through deployment and ongoing production operation.
•Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Data Science, AI, or a related quantitative field (or equivalent practical experience).
•Strong Python development skills for tested, maintainable production code, APIs, automation, and operational scripts, with Git-based development and code review practices.
•Practical ML experience with libraries such as Scikit-learn, TensorFlow, and/or PyTorch, including model development, evaluation, and core algorithm concepts.
•Hands-on MLOps and platform engineering experience with Docker and Kubernetes (or managed containers), plus Terraform/infrastructure-as-code and major cloud exposure (GCP preferred).

Education:Bachelor's

Skills:Engineering rigorProblem-solvingConsulting mindsetCommunicationCreative problem-solving

Languages:English

Tech Stack:PythonAPIsGitGitHub ActionsGitLab CIAzure DevOpsCloud BuildTerraformTerraform modulesSQLPandasNumPyScikit-learnTensorFlowPyTorchDockerKubernetesHelmArgo CDMLflow

Company Brief

Endava Technology

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Website LinkedIn