Software Architect - ML / AI / Gen AI

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, cybersecurity, 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.

Role We are looking for a Software Architect (Machine Learning).

The ideal candidate should have a Masters or Ph.D.

degree in Computer Science with 8 Plus years of experience in Machine Learning & AI.

Responsibilities Lead the design and architecture of machine learning solutions for complex business problems.

Collaborate with business stakeholders to understand their requirements and define the overall technical strategy, including model selection, data pre-processing, feature engineering, and model evaluation.

Design and implement scalable and efficient data pipelines to collect, preprocess, and store large volumes of data for machine learning projects.

Develop data transformation and feature extraction processes to prepare data for machine learning model training and deployment.

Lead the development of advanced machine learning models using state-of-the-art algorithms, such as deep learning, reinforcement learning, and other cutting-edge techniques.

Optimize model performance through hyperparameter tuning, model validation, and feature selection.

Drive the deployment of machine learning models in production environments, ensuring scalability, reliability, and security.

Implement monitoring and logging mechanisms to capture and analyze model performance data.

Make necessary adjustments to ensure optimal performance and accuracy.

Provide technical leadership and mentorship to a team of data scientists, engineers, and other stakeholders.

Guide and mentor junior team members, provide technical expertise and advice, and drive innovation in the field of machine learning.

Stay updated with the latest developments in the field of machine learning and artificial intelligence.

Identify and evaluate new technologies, tools, and techniques for improving machine learning models and systems.

Drive innovation and experimentation to push the boundaries of machine learning capabilities.

Collaborate closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to understand requirements, provide technical guidance, and ensure successful implementation of machine learning solutions.

Collaborate with business stakeholders to identify new opportunities for leveraging machine learning for business success.

Create documentation, technical specifications, and reports related to machine learning solutions, including model design, data pipeline architecture, deployment process, and performance metrics.

Present findings and recommendations to stakeholders in a clear and concise manner.

Requirements Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field.

8+ years of relevant experience in machine learning and artificial intelligence.

Proven experience in designing, developing, and implementing advanced machine learning solutions for complex business problems.

Strong programming skills in languages such as Python, R, or Java, and deep understanding of machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.

Extensive experience with machine learning algorithms, including deep learning, reinforcement learning, and other cutting-edge techniques.

Strong knowledge of data preprocessing, feature engineering, and data visualization techniques.

Excellent understanding of machine learning model performance metrics and optimization techniques.

Experience with designing and implementing scalable data pipelines and working with big data technologies.

Proven experience with deploying machine learning models in production environments, and implementing monitoring and logging mechanisms for performance analysis.

Strong leadership and mentoring skills, with the ability to provide technical guidance and mentor junior team members.

Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.

Strong communication and presentation skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.

Proven ability to drive innovation, research new technologies, and push the boundaries of machine learning capabilities.

Ethical mindset and commitment to ensuring compliance with data privacy, security, and ethical considerations in machine learning projects.

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