Sr.Machine Learning Engineering

Roles and Responsibilities

  • As a Senior ML Engineer you will: Lead development of services and infrastructure at the  intersection of machine learning, big data, and distributed systems.  
  • Our products and services empower hundreds of science teams across Amazon to deliver  machine learning at scale for ML model training, Feature engineering and Data quality  monitoring.  
  • You will be at the center stage for managing machine learning lifecycle and operations  using AWS/GCP AI services, DL compute resources, and our core search backend services  for query understanding, semantic matching, and relevance ranking.  
  • You will build scalable data-intensive infrastructure that processes huge amounts of logs,  catalogs, transactional data, and telemetry signals.  
  • By doing so, we enable teams to become more data-driven and build robust and explainable  ML services.  
  • Hands on experience on Numpy, Pandas, NLTK, TensorFlow, PyTorch and Keras. Caffe  Supervised Machine Learning Algorithms,Deep Learning Models (CNN, RNN, LSTM,  BERT, NLU and YOLO) Cloud Platforms (AWS/GCP) - Sagemaker or Vertex AI  Experience in Data Wrangling and PySpark(Good to have knowledge over EMR and Glue)  Excellent skills developing in Python as well as significant experience working in Linux  environments. Experience with containerizing applications using Docker Experience in  SQL and at least one NoSQL data store Elasticsearch, MongoDB, Cassandra and HBase  Experience in handling branch based deployments. Knowledge over MLFlow and  Kubeflow. Optimization of Multiple GPUs. Research, develop, and implement state-of the-art techniques in the field of Large 
  • Language Models (LLM) and Generative AI. 
  • Collaborate with cross-functional teams to design and execute projects that leverage LLMs  for various applications, such as text generation, summarization, translation, and more.
  • Stay up-to-date with the latest advancements in AI, machine learning, and generative models, and apply this knowledge to enhance existing models and methodologies.
  • Analyze and fine-tune model performance through experimentation, iteration, and data driven insights. 
  • Provide technical leadership and mentorship to junior team members, fostering a culture  of innovation and continuous learning. 
  • Contribute to research publications, whitepapers, and presentations to showcase the  organization's expertise in the field. 
  • Collaborate with product teams to integrate AI solutions into real-world applications and  platforms.

Technical Expertise

Design and Develop:

  • Lead the design, get your hands dirty and write code, and ultimately deploy big data and  machine learning services. These services define the foundation of our search R&D  processes, supporting science, product development and production of the world’s largest  product search engine. 
  • Possess expert knowledge in performance, large scale distributed system scalability,  system architecture, and engineering best practices. 
  • Workable knowledge of AI and ML best practices for model building, automation and  neural network enrichment iterative learning Operational Excellence. 
  • Obsess over operational excellence, evaluate system performance, security, design system  metrics and driving quality improvement, Obsess over customer needs and satisfaction.

Team Responsibilities: 

  • Clear communication with product managers and other engineers regarding project  timelines, delays, advancements, and progression. 
  • Mentor other engineers, defining our challenging technical culture, and helping to build a  team with “black box” problem-solving skill Strong time management skills. 

Job Qualifications: 

  • Masters or Bachelor’s degree in Computer Science/IT, software engineering or data  science, is recommended.  
  • Master’s degree in Artificial Intelligence a plus.  
  • Cloud(GCP/AWS), PyTorch,Tensorflow Python, R, or OpenAI/Gen AI is a plus  • 5 years of experience with software development in one or more programming languages,  and with data structures/algorithms. 
  • 3 years of experience testing, maintaining or launching software products, and 1 year of • experience with software design and architecture. 
  • 4 years of experience with ML/AI algorithms and tools, deep learning or natural language • processing.  
  • 1-2 year of experience in a technical leadership role. 
  • Experience developing accessible technologies. 
  • 1 year of experience in a technical leadership role

Get in touch.
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