Machine Learning Engineering Lead

16 hours ago


Lahore, Punjab, Pakistan Cinnova Technologies, LLC Full time

We're looking for an experienced professional to join our team as a Machine Learning Engineer. The ideal candidate will have a strong background in AI/ML model development and deployment, as well as experience working with large-scale datasets.

Responsibilities:

  • Design and develop machine learning models and AI-driven solutions to address complex business challenges.
  • Collaborate with cross-functional teams to define project requirements and integrate AI/ML solutions into business workflows.
  • Develop and deploy secure and scalable ML pipelines, leveraging MLOps best practices for continuous integration and deployment.
  • Monitor, evaluate, and refine model performance using A/B testing, drift detection, explainability, and adversarial robustness techniques.
  • Implement AI security best practices, including adversarial attack detection, model integrity verification, and bias mitigation.
  • Stay updated with LLMs, generative AI, retrieval-based AI trends, and secure AI development methodologies.
  • Deploy and manage AI/ML models on cloud platforms such as AWS, Azure, or GCP, ensuring compliance with secure AI governance frameworks.
  • Work with vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) and retrieval frameworks (e.g., LangChain, LlamaIndex).
  • Build and optimize secure APIs, ensuring protection against data leaks, prompt injection attacks, and unauthorized access.

Requirements:

  • 2+ years of experience in AI/ML model development and deployment.
  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field.
  • Strong programming skills in Python (preferred), R, or Java.
  • Hands-on experience with ML frameworks like TensorFlow, PyTorch, or Keras.
  • Expertise in natural language processing (NLP), computer vision, deep learning, and LLMs.
  • Proficiency in retrieval-augmented generation (RAG), embedding models, and vector databases (FAISS, Pinecone, Weaviate, ChromaDB).
  • Experience with cloud AI services (AWS SageMaker, Azure AI, Google AI Platform).
  • Strong understanding of Hugging Face Transformers, Model Hub, and tokenizers for model fine-tuning and deployment.
  • Familiarity with big data tools such as Hadoop, Spark, or Kafka (preferred).
  • Strong understanding of adversarial ML attacks, model explainability, AI governance, and bias mitigation techniques.
  • Knowledge of security best practices for AI, including prompt injection protection, data anonymization, and secure model deployment.
  • Strong foundation in algorithms, data structures, and model evaluation techniques.
  • Proven ability to deliver end-to-end AI/ML projects, from concept to production, with a focus on secure and responsible AI.
  • Strong analytical and problem-solving skills with attention to detail.
  • Excellent communication skills to collaborate with teams and present findings.
  • Ability to work on-site and manage multiple projects effectively.


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