Gen AI Engineer

4 weeks ago

Lahore, Punjab, Pakistan Code Upscale Full time

1 week ago Be among the first 25 applicants

Direct message the job poster from Code Upscale

Co-Founder @Code Upscale | AI Transformation Leader | Helping Companies to Adopt Cloud and AI

Role Snapshot

Own end-to-end delivery of generative-AI solutions—data ingestion, model training, deployment, and post-release optimization. You'll join a small team shipping production-grade ML at scale for our clients.

Core Responsibilities
  • Design, train, fine-tune, and evaluate LLMs or diffusion models for text, image, and multi-modal use cases.
  • Build data pipelines for collection, cleansing, augmentation, and labeling (Python, Spark, or equivalent).
  • Integrate GenAI services into customer-facing products via REST/GraphQL and streaming APIs.
  • Instrument robust monitoring—drift detection, automatic retraining triggers, usage analytics, and A/B testing.
  • Collaborate with product and design to translate fuzzy requirements into measurable ML metrics (precision, recall, BLEU, ROUGE, etc.).
  • Contribute to internal libraries, CI/CD workflows, and security reviews.
  • Present technical findings and roadmap recommendations to stakeholders with concise, data-backed insights.
Minimum Qualifications
  • 3 + years hands-on ML engineering; at least 18 months rooted in generative models.
  • Proven track record shipping at least one GenAI feature to production (LLMs, diffusion, or audio).
  • Strong Python and deep-learning stack expertise (PyTorch or TensorFlow, Hugging Face, Weights & Biases).
  • Proficiency with cloud GPU workflows on AWS, GCP, or Azure—including Terraform or Pulumi for IaC.
  • Solid grounding in statistics, optimization, and modern ML architectures (transformers, VAEs, LoRA, quantization, RAG).
  • Comfortable with SQL/NoSQL datastores and container orchestration (Docker, K8s).
Bonus Points
  • Experience compressing and distilling large models for mobile or edge deployment.
  • Familiarity with reinforcement learning from human feedback (RLHF) pipelines.
  • Contributions to open-source GenAI projects or published research.
  • Knowledge of privacy-preserving ML (federated learning, differential privacy).
  • Competence in TypeScript or Python for backend services.
Seniority level
  • Seniority levelMid-Senior level
Employment type
  • Employment typeFull-time
Job function
  • Job functionEngineering and Information Technology
  • IndustriesSoftware Development

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