AI & Machine Learning Engineer (Production Systems & Pipelines)

NeuralSurge AI is seeking a Senior AI & Machine Learning Engineer to lead the technical development and ownership of our end-to-end intelligence pipelines. This role involves bridging the gap between experimental data science models and customer-facing full-stack applications. You will work on deploying open-weight foundation models on dedicated compute runtimes, optimizing inference performance, building advanced retrieval architectures, and collaborating closely with our MERN (Node.js/React) software engineering team. The position is based onsite in Lahore, Pakistan, at Etihad Town, Phase-1, and requires a minimum of three years of professional engineering experience.

Key Responsibilities

- End-to-End Pipeline Execution: Architect, deploy, monitor, and scale production AI/ML pipelines covering data ingestion, custom chunking, embedding generation, vector indexing, inference orchestration, and evaluation loops.

- Inference Serving & Runtimes: Deploy, scale, and profile open-source foundation models such as Llama, Qwen, Mistral, and Gemma on GPU infrastructure using high-throughput runtimes including vLLM, Triton Inference Server, Ollama, and TensorRT-LLM.

- Pipeline Engineering: Design and build custom retrieval systems, rerankers, semantic query routers, and agentic reasoning loops using raw Python and vector databases, avoiding brittle black-box abstractions.

- Model Fine-Tuning & Weight Adaptation: Lead parameter-efficient fine-tuning workflows such as PEFT, LoRA, QLoRA, Unsloth, and TRL, along with alignment strategies to tailor open-source models to domain-specific enterprise needs.

- MERN Stack & Microservices Integration: Work closely with the MERN engineering team to expose low-latency, asynchronous FastAPI endpoints, streaming protocols (WebSockets / Server-Sent Events), and background worker contracts (Redis / Celery / BullMQ).

- Dual-Track Delivery:
- *Product Track:* Build and harden core intelligence layers powering NeuralSurge’s proprietary SaaS platforms.
- *Services Track:* Architect secure, compliant, and sovereign/air-gapped AI pipelines for enterprise client engagements.

- Performance & Cost Optimization: Profile inference latency, token economics, batching, and GPU VRAM usage using quantization techniques such as AWQ, GPTQ, and GGUF to maximize throughput while minimizing compute overhead.

- LLMOps & Quality Engineering: Implement automated evaluation suites (RAGAS, DeepEval, LLM-as-judge), latency tracing, and deterministic guardrails to prevent hallucination, data leakage, and model drift.

Required Qualifications

- Bachelor’s degree in Computer Science or related field with at least 3 years of verified commercial engineering experience delivering production-grade Python backend services or applied AI/ML systems.

- Proven experience in deploying and maintaining AI/ML pipelines in production environments.

- Strong proficiency in Python programming, model fine-tuning, and GPU-based inference optimization.

- Familiarity with microservices architecture and asynchronous API development.

Preferred Qualifications

- Practical exposure to multimodal AI architectures including Computer Vision (YOLO), voice agents (Whisper), or diffusion models.

- Experience designing and implementing air-gapped or on-premise sovereign AI infrastructure for enterprise clients.

- Active contributions to open-source machine learning tooling, custom frameworks, or published research.

NeuralSurge AI offers the opportunity to work on cutting-edge AI infrastructure and collaborate with a dynamic engineering team in a fast-growing company. This is a full-time onsite role based in Lahore, Pakistan. Candidates with a passion for building scalable, high-performance AI systems and a drive for innovation are encouraged to apply.