AI/ML Engineer

Responsibilities

• Design, build, and deploy complete AI/ML systems from experimentation to production.
• Work with LLMs, neural networks, RAG pipelines, agentic AI frameworks, and scalable data workflows.
• Partner with product and engineering teams to prototype and ship several AI-driven features and products each month.
• Optimize models for performance, scalability, cost efficiency, and real-world constraints.
• Provide production support for deployed models and continuously iterate to improve outcomes.
• Stay ahead of emerging AI technologies and integrate new tools to accelerate development cycles.

Qualifications

• 4+ years of hands-on experience in ML engineering or applied data science.
• Strong expertise with LLMs, neural networks, RAG architecture, and agent-based AI systems.
• Solid background in data pipeline engineering, ETL, orchestration, and distributed processing.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Familiarity with modern AI stacks, including LangChain, Hugging Face, vector databases, and related tools.
• Proven experience deploying ML systems in cloud environments such as AWS, Azure, or GCP.
• Strong analytical thinking, problem-solving mindset, and ability to thrive in iterative, high-velocity product cycles.
• Bonus: Experience shipping multiple AI products within short development timelines.

Job Type: Full-time

Pay: Rs300,000.00 - Rs400,000.00 per month

Application Question(s):

• Walk me through the most complex AI/ML system you’ve built end-to-end. What problem did it solve, what stack did you use, and what specifically was your contribution?
• Have you deployed an LLM, RAG pipeline, or agentic workflow into production? Describe the architecture, latency constraints, and how you handled scalability or cost optimization.
• Explain a time you optimized a model or data pipeline for performance. What metrics improved and how did you achieve it?
• Tell me about a recent AI framework, tool, or technique you adopted that significantly accelerated your delivery. Why did you choose it and what impact did it have?
• You’re tasked with shipping two AI-driven product features in a single month. What’s your approach from discovery to deployment?
• How much experience do you have with Rag Structure, LLM's, Vectorization?
• Current salary
• Desired salary
• Notice Period Duration
• Are you availabile for an online session to understand your background better between 10pm to 3am PKT ?

Work Location: In person