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Open nowFirst seen 17 hours ago

AI Scientist – Mid Level

PrimeStaff Management Service Pte Ltd51 open roles

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Your applicationOpen nowAI Scientist – Mid LevelPrimeStaff Management Service Pte Ltd

  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 PrimeStaff Management Service Pte Ltd's own form.

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: first seen 17 hours ago

The posting

About us: At our reputed company, we don't just build Vehicles, we create great software. We develop tomorrow's mobility together in our product lines, pushing the digitization of the institution forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work. IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together. We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the company. Our workplace is anywhere with a fast connection whether remotely at home, at your favorite café, or at our integrated company office.

Key Responsibilities / Job Description

  • Design and implement end-to-end AI systems including inference pipelines, agent workflows, and tool-calling architectures
  • Build and manage context orchestration for LLMs (system prompts, memory, retrieval, and structured inputs)
  • Engineer latency-aware and cost-efficient fallback strategies across models and providers.
  • Develop backend services for prompt routing, response handling, and tool execution (Python / Node.js or similar)
  • Implement observability for AI systems: logging, metrics, tracing, and quality monitoring
  • Maintain CI/CD pipelines for AI services and ensure safe, repeatable deployments
  • Design, develop, integrate and deploy AI-powered software solutions into productive, scalable enterprise environments
  • Translate business and product requirements into robust AI system designs and architectures
  • Collaborate closely with data scientists, software engineers, product owners, and business stakeholders
  • Ensure compliance with applicable rules in the areas of data protection, AI governance, and IT security
  • Document architectures, models, and implementation decisions in a target-group adequate form

Required Skills & Qualifications

  • 2+ years in software engineering, including hands-on experience with AI/ML or LLM systems
  • Bachelor's/Master's in Computer Science, Data Science, or related fieldExperience with LLMs, prompt engineering, tools, and agent-style architecture
  • Experience in Agile, product-driven teams
  • Familiarity with enterprise-scale architectures, DevOps, and CI/CD

Specific Knowledge / Skills

  • Proficient in Python
  • Experience with LLMs, NLP, or semantic models
  • Skilled in fine-tuning and evaluating LLMs, including quality and failure modes
  • Able to build automated AI pipelines for training, testing, deployment, and monitoring
  • Familiar with cloud platforms and containers
  • Analytical thinker; committed to robust, reliable software
  • Strong communicator with a customer focus
  • Results-driven, emphasizing scalable, maintainable solutions
  • Actively follows and adopts new AI advancements

Bonus Points if you have

  • Experience with LLM APIs such as OpenAI, Claude, or similar providers
  • Hands-on work with RAG systems, vector databases, and embedding pipelines
  • Exposure to model safety, guardrails, or responsible AI practices

Technical

  • Python
  • SQL / NoSQL
  • REST APIs and backend integration
  • LLM-based solution development
  • Spark / Apache ecosystem
  • Cloud Computing
  • GPU orchestration and cost optimization
  • Containerization (Docker, Kubernetes)
  • CI/CD and DevOps tooling
  • Scalable data and AI architectures
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