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Open nowPosted today

Senior ML /AI

EXCELTECH COMPUTERS PTE. LTD.

Pay
SGD 8,000 – SGD 12,000 a month
Where
East, Singapore
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Your applicationOpen nowSenior ML /AIEXCELTECH COMPUTERS PTE. LTD. · East, Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on EXCELTECH COMPUTERS PTE. LTD.'s own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.4% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.4%7 days
  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted today

The posting

Senior ML /AI Work location- Paya Lebar

The ML/AI Engineer sits within the DSAD Platform and Architecture Team and is responsible for productionising,

operating and improving machine-learning and AI workloads on the SWDA data platform using AWS and Databricks.

Experience: Typically 4–7 years of relevant software, data or ML engineering experience, including hands-on delivery

and operation of ML/AI systems beyond prototype stage. Candidates with fewer years but strong evidence of end-toend

production ownership may also be considered.

B. Technical & Professional Competencies

Essential (Must-Have)

• Strong Python and software-engineering capability, including APIs, packaging, automated testing, Git, code

review, debugging and modular design.

• Hands-on experience with Databricks and MLflow for experiment tracking, model registry, workflow orchestration

or model serving.

• Strong hands-on experience with Spark/PySpark and SQL, including distributed data processing, query

optimisation, partitioning, joins, incremental processing and troubleshooting data pipelines.

• Experience designing and implementing lakehouse or data-lake pipelines using Databricks, Delta Lake and AWS

S3, including Bronze, Silver and Gold data-layer patterns.

• Experience with data modelling, schema design, data contracts, metadata, lineage, data-quality validation and

reconciliation for production analytics and ML datasets.

• Experience orchestrating batch or streaming workflows using Databricks Workflows, AWS Glue, Step Functions,

EventBridge, Apache Airflow or an equivalent enterprise orchestration tool.

• Hands-on AWS data and cloud engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS,

ECR, ECS/EKS, Lambda, Step Functions, EventBridge, CloudWatch, API Gateway, Secrets Manager, Redshift,

MSK/Kinesis or equivalent approved services.

• Experience with Docker, infrastructure as code such as Terraform, and CI/CD platforms such as GitLab CI,

GitHub Actions, Jenkins or Harness.

Posting text belongs to the employer. Removal requests: contact us.

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