Principal AI Engineer

Principal AI Engineer - Computer Vision (2 years contract)
Principal AI Engineer - Computer Vision (2 years contract)
Get AI-powered advice on this job and more exclusive features.
We build autonomous AI agents that partner with computer‐vision engineers to curate data, train models, and ship services—on time, every sprint. A transparent roadmap, bi‐weekly reviews, and robust CI/CD keep us laser‐focused on production impact.
This is a 2-year contract position (convertible if good performance) based in Singapore.
Key Responsibilities
Agent Framework & Libraries
Architect modular Python libraries and a CLI that expose core agent primitives—task graphs, skills, memory, and tool interfaces.
Orchestration & Scheduling
Implement a scalable orchestration layer (Celery, Argo Workflows, Prefect, or similar) that runs multi‐step CV pipelines with retry, rollback, and SLA guarantees.
Integrate vector and hybrid search stores so agents can retrieve data during execution.
Create CLI utilities and REST/gRPC APIs that let engineers trigger, inspect, and debug agent runs.
Maintain CI/CD pipelines, comprehensive test suites, and infrastructure‐as‐code so the agent platform ships reliably on a bi‐weekly cadence.
Integrate CV Toolkits
Wrap best‐in‐class vision components (OpenCV, TorchVision, MMDetection, Ultralytics YOLO, Albumentations, etc.) so agents can call data‐prep, augmentation, model‐zoo, and metric utilities on demand to meet user requirements.
Must-Have Skills
Solid engineering foundation – 5 + years writing production software (ideally Python), strong grasp of algorithms, data structures, Git workflows, and code‐review best practices.
Agent frameworks – hands‐on experience designing or extending agent stacks such as LangChain, AutoGen, CrewAI, or custom in‐house task‐graph engines.
Orchestration at scale – proficiency with a workflow scheduler or task queue (Prefect, Argo Workflows, Airflow, Dagster, Celery) and the patterns for retry, rollback, and SLA tracking.
Computer‐vision pipeline know‐how – practical exposure to training and evaluating CV models (classification, detection, segmentation) and understanding of data‐quality pitfalls.
Evaluation & observability – ability to build automated test/evaluation harnesses using pytest, MLflow, wandb, or equivalent, and expose metrics via Prometheus/Grafana or OpenTelemetry.
Vector & hybrid search – experience integrating stores such as Pinecone, Weaviate, pgvector, or FAISS to power agent memory and retrieval workflows.
Model serving & packaging – familiarity with TorchServe, Triton, BentoML, ONNX Runtime, or similar frameworks, plus Docker/Kubernetes fundamentals.
CI/CD & IaC – competence setting up GitHub Actions/GitLab CI pipelines and Infrastructure‐as‐Code (Terraform, Pulumi) to keep releases predictable.
Cloud fluency – production deployments on one or more providers (AWS, GCP, Azure) and an eye for cost/performance trade‐offs.
Clear communication – comfort writing design docs/RFCs and mentoring peers on agent architecture, testing, and deployment best practices.
Nice-to-Have Skills
Portfolio of AI/Computer Vision/Agent projects or open-source contributions
ML observability tools familiarity (e.g., Grafana or Datadog)
Seniority level
Seniority level Mid-Senior level
Employment type
Employment type Contract
Job function
Job function Information Technology
Industries Defense and Space Manufacturing
Referrals increase your chances of interviewing at ST Engineering by 2x
Sign in to set job alerts for "Artificial Intelligence Engineer" roles.
Junior Software Engineer (AI Training Provided)
Johor Baharu, Johore, Malaysia 14 hours ago
Artificial Intelligence Developer | Permanent
Queenstown, Central Singapore Community Development Council, Singapore 6 months ago
Applied Machine Learning (ML) / AI Software Engineer
AI Engineer Lead at Aios Medical — Remote, $80k-$120k/year inc equity
We're unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr