Junior Machine Learning

3 days ago

Lahore, Punjab, Pakistan Harris Silicone & Glass Pvt. Ltd. Full time 600,000 - 1,200,000 per year

Junior Machine Learning / AI Engineer (Computer Vision & Generative AI – LLMs)

Location: On-site

Experience: 6 months – 1 year

Type: Full-time

About the Role

We're looking for a passionate Junior ML/AI Engineer with foundations in Computer Vision and Generative AI using Large Language Models (LLMs).

You'll work on real-world AI systems combining visual intelligence (face recognition, detection, tracking) with language understanding and generation (LLM-based automation, chat systems, data agents).

If you're excited by models like GPT, LLaMA, Mistral, or Claude, and love integrating vision + language to create smart systems — this role is for you

Key Responsibilities

· Build and optimize computer vision pipelines (detection, tracking, face recognition, etc.) using frameworks like OpenCV, YOLO, and InsightFace

· Develop LLM-powered applications (chatbots, summarizers, document understanding tools, etc.)

· Fine-tune and prompt LLMs (OpenAI GPTs, LLaMA, Mistral, Phi, etc.) for domain-specific use cases

· Integrate ML and LLM models into scalable backends (FastAPI, Flask)

· Collaborate on multimodal AI projects combining image and text intelligence

· Deploy models efficiently using Docker or ONNX Runtime

· Experiment with open-source models from Hugging Face and LangChain, LangGraph

Required Skills & Tools

· Core ML & AI:

· Python, NumPy, Pandas, Scikit-learn

· PyTorch or TensorFlow

· OpenCV, Mediapipe, InsightFace, YOLOv8

Generative AI / LLMs:

· Hugging Face Transformers

· OpenAI API / Ollama / LLaMA / Mistral / Phi

· LangChain, LangGraph, LlamaIndex, or Haystack

· Prompt engineering and few-shot tuning

· Tokenization, embeddings, and retrieval-augmented generation (RAG)

· Knowledge of vector databases (FAISS, Chroma, Pinecone)

Development & Integration:

· FastAPI or Flask

· REST APIs, JSON, async programming

· Docker, Git, and basic CI/CD

· Bonus Skills (Nice to Have):

· Fine-tuning LLMs with LoRA or PEFT

· GPU usage (CUDA, cuDNN)

· Familiarity with MLOps tools (Weights & Biases, MLflow, DVC)

Qualifications

· Bachelor's degree in Computer Science, AI, Data Science, or related field

· 6 months – 1 year of practical experience (internship, research, or projects)

· Strong understanding of ML fundamentals and interest in generative AI

Why Join Us

· Work on real applied AI projects in vision and language

· Learn directly from senior AI engineers and researchers

· Gain experience with state-of-the-art LLM frameworks and tools

· Access to GPU-powered systems, real-world data, and production pipelines

· A collaborative, innovative, and growth-driven culture

Apply Now:

Job Type: Full-time

Work Location: In person

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