
Principal/Staff Software Consultant
4 weeks ago
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 ofdeveloping 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
- Advanced degree (Ph.D. or Master's) in Computer Science, Machine Learning, or a related field
- Proven experience with Amazon Personalizesetup, 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)
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