Principal/Staff Software Consultant - Machine Learning + AWS SageMaker

Company Overview
10Pearls is an end-to-end digital technology services partner helping businesses utilize technology as a competitive advantage. We help our customers digitalize their existing business, build innovative new products, and augment their existing teams with high-performance team members. Our broad expertise in product management, user experience/design, cloud architecture, software development, data insights and intelligence, cyber security, emerging tech, and quality assurance ensures that we are delivering solutions that address business needs. 10Pearls is proud to have a diverse clientele including large enterprises, SMBs and high-growth startups. We work with clients across industries, including healthcare/life sciences, education, energy, communications/media, financial services, and hi-tech. Our many long-term, successful partnerships are built upon trust, integrity and successful delivery and execution. 

Requirements
We are looking for a Principal/Staff Machine Learning Engineer. The ideal candidate should have a Master’s degree in Computer Science with 5 – 8 years of developing machine learning models, with a strong portfolio in Computer Vision and LLMs.

Responsibilities

• Lead the design, development, and deployment of generative AI models, large language models, and retrieval-augmented generation systems.
• Conduct cutting-edge research in AI, contributing to advancements in image and video analysis, object detection, segmentation, and NLP.
• Collaborate with product teams to integrate AI/ML technologies into new and existing products.
• Develop and implement machine learning algorithms and models using state-of-the-art techniques and best practices.
• Optimize models for performance, scalability, and efficiency on cloud platforms.
• Implement MLOps practices to streamline the machine learning lifecycle, including model training, deployment, monitoring, and maintenance.
• Mentor and lead a team of machine learning engineers, fostering a culture of technical excellence.
• Optimize machine learning workflows for improved model performance and efficiency.
• Develop and maintain robust data pipelines for model training and inference at scale.
• Implement rigorous model testing and validation to ensure high-quality deployments.
• Contribute to the company's intellectual property through innovative research, patents, and publications.
• Work closely with cross-functional teams, including data scientists, analysts, and other developers, to understand data requirements and implement effective solutions. 
• Stay abreast of industry trends and emerging technologies in AI to maintain a competitive edge.
• Communicate technical concepts effectively to stakeholders and influence strategic decisions with ML insights.

Requirements

• Advanced degree (Ph.D. or Master's) in Computer Science, Machine Learning, or a related field

• Proven experience with Amazon Personalize: setup, configuration, optimization, and implementation of recommendation use cases.

• Strong hands-on experience with AWS SageMaker, including training and deploying custom machine learning models.

• Proficiency in developing recommendation systems using techniques like collaborative filtering, deep learning, and reinforcement learning.

• Experience with data pipeline development (ETL/ELT) for capturing user behavior, video viewership, and conversion data.

• Ability to design and deploy real-time, low-latency inference endpoints using AWS services such as Lambda and API Gateway.

• Tools & Technologies

• AWS ecosystem (SageMaker, Personalize, Lambda, API Gateway)

• Data engineering tools and scripting (e.g., Python, SQL)

• ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)

• Monitoring and visualization tools (e.g., CloudWatch, dashboards)