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) Powered by JazzHR