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Machine Learning Engineer

2 months ago

Visakhapatnam, India PVAR SERVICES Full time

Job Title: AI/ML Engineer

Experience: 4+ years

Budget: 35 LPA

Location: Gurgaon

Industry: Tech Product


Position Overview: We are looking for a skilled and driven AI/ML Engineer to become a key member of our innovative team. The ideal candidate will bring a solid foundation in machine learning, data analytics, and software engineering, and will take charge of developing and implementing cutting-edge AI solutions to tackle complex challenges.


Key Responsibilities:

  • Design, build, and refine deep learning models for Text2SQL, Text-to-Speech (TTS), and image generation tasks.
  • Develop and optimize Generative AI models utilizing frameworks such as GPT, BERT, Anthropic, T5, and more.
  • Work with Generative Adversarial Networks (GANs) like Wav2Lip and LipSync.
  • Knowledge of NVIDIA frameworks, including Triton and Omniverse, is essential.
  • Integrate AI models into various applications, ensuring scalability and high performance.
  • Tailor models for specific industries or scenarios to enhance accuracy and operational efficiency.
  • Stay updated on the latest machine learning and natural language processing (NLP) advancements, including diffusion models for image generation tailored to the fashion industry.
  • Deploy, oversee, and maintain AI solutions in production settings.
  • Ensure AI models align with ethical guidelines and minimize bias.
  • Develop Retrieval-Augmented Generation (RAG)-based systems to improve model performance and information retrieval.
  • Work with diverse database systems, such as vector and graph databases, to support AI functionalities.
  • Apply basic computer vision and image processing techniques to relevant initiatives.
  • Conduct AI model benchmarking using industry-recognized metrics and datasets to measure and improve performance across various tasks.


Skills and Qualifications:

  • 4+ years of experience in AI engineering with a focus on Large Language Models (LLMs) and Generative AI.
  • Proficiency in programming languages such as Python, and frameworks like TensorFlow, PyTorch, and Keras.
  • In-depth experience with training and fine-tuning LLMs (e.g., GPT-3, BERT, T5) and a strong understanding of their architecture.
  • Practical knowledge of NLP techniques and deep learning frameworks.
  • Strong grasp of transformer models and their practical applications.
  • Familiarity with cloud services such as AWS, GCP, or Azure for deploying models.
  • Experience handling large datasets and optimizing models for better performance.
  • Excellent problem-solving and analytical skills.
  • Familiarity with ML Ops practices is an advantage.
  • Strong collaboration and communication abilities.
  • Experience with RAG systems and related knowledge bases.
  • Competency in using various database types, including relational, vector (e.g., Pinecone, Faiss), and graph databases (e.g., Neo4j, Amazon Neptune).
  • Basic skills in computer vision and image processing with libraries such as OpenCV and PIL.


Benchmarking Expertise:

  • Deep understanding of AI benchmarking methods and experience with well-known benchmarks across AI tasks, such as:
  • Natural Language Processing: GLUE, SuperGLUE, SQuAD
  • Machine Translation: WMT, BLEU score
  • Text Summarization: ROUGE
  • Image Classification: ImageNet
  • Object Detection: COCO, Pascal VOC
  • General Language Understanding: MMLU (Massive Multitask Language Understanding)
  • Capability to design and execute custom benchmarks for unique use cases and industry requirements.