Major Focus: Data Engineering (Algorithms & Systems), Machine Learning, Computer Vision, NLP

Related Focus: Distributed Systems, Scalable System Design, Software Engineering (Backend), Databases (SQL, NoSQL), Graph Algorithms & Databases, Approximate Algorithms, Information-Retrieval, AI Fairness.

Mini Focus: DevOps, Cloud, Optimization, Visualization, Management (Organizational, Project, Leadership)

Dynamic, independent, self-motivated, adaptable, and transformational engineering professional with demonstrated skills in building high-quality Artificial Intelligence, Data Sciences, and Analytics products and solutions. Extensive industrial experiences in engineering scalable Machine & Deep Learning, Natural Language Processing, and Computer Vision-based products and solutions. Advanced exposure in software and cloud engineering. Expert in unveiling deep insights from messy, complicated data and in building sophisticated data engineering pipelines supporting end-to-end automation, self-serve analytics. Highly skilled in project management, communication, pair-programming, and in working with distributed cross-functional teams. A demonstrated track record of surpassing challenging expectations and orchestrating professionalism of the highest quality makes me a competitive applicant fit for a suitable role in engineering teams.

My research interests are in engineering advanced intelligent solutions (using Machine/Deep Learning, Natural Language Processing, Computer Vision, and Reinforcement Learning) geared towards large-scale adoption and usage. Besides, I have serious proficiency in Optimization Programming, Predictive and Prescriptive Analytics, and Security Engineering.

Mission statements:

• Move things at light speed in organizations when things sometimes move at a snail's pace.

• Working with totally abstract ideas and shaping them into reality.

• Drive crisp, clear, and candid communication at all times.

• Fail, but fail fast. Never hesitate to accept failures and learn to correct shortcomings.

• Build deep expertise in the industry, organization, and people.

1. Drove platform engineering innovations for decentralized Intelligent Pricing Hierarchy platform with state-of-the-art high-frequency time series and recommendation models.

2. Independently and in-teams supported production for critical AI models deployed across the globe, hybrid cloud.

3. Architected, Engineered several key modules in the in-house chaos automation delivery platform with capabilities to run 100,000 concurrent large-scale experiments with ultra-low latency.

4. Actively collaborated, drove meetings for formulating novel use-cases and new data platforms initiatives across geographies, business units.

1. Contributed to full-stack architecture, engineering of deep anomaly segmentation, detection algorithms. Lead engineering, adoption of the associated data engineering pipelines, and self-serve dashboarding solutions.

2. Lead architecture, production of early threat modeling solutions for the in-house ingestion analytics platforms. Contributed to product experimentation, metrics development. Lead architecture, production of intelligent inventory management solutions, and drove key-experimentation efforts in engineering KPIs, metrics. Independently architected, supported pre-production of automated asset model collations, metrics.

3. Contributed to architecture, production of real-time deep NLP solutions with the implementation of novel, production-grade VADER algorithm & Multi Attention Network, based aspect-level sentiment modeling.

4. Actively collaborated in use-case formation/enrichment, data modeling & acquisition across geographies, business verticals. Remarkable proficiency in time-critical product engineering deliveries. Awarded with promotion, recommendations for driving consistent excellence in engineering.

5. Drove several units' architecture developmental efforts in hybrid (cloud, on-premises) data sciences & engineering, analytics (predictive, prescriptive), DevOps, and full-stack software engineering. Extensive production experience in owning four end-to-end critical DS engineering solutions as a full-stack Data Scientist.

1. Lead architecture, engineering of novel distributed NLP system for smart-home, scheduling & delivery big-data platform supporting storage, analytics, and Data Sciences of media services. Actively contributed to software engineering, cloud-based cloud-architectures (including DevOps, Networking, Security), and novel voice-based user interfaces.

2. Successfully lead the production of three full-stack intelligent solutions and in-production experimentations. Assisted as product-owner, subject-matter expert in stakeholder management and novel use-case modeling across teams, business verticals, geographies.

3. Collaborated in new architecture development and characteristics studies for new-products and in-development utilities. Lead development of novel product metrics for commercial smart-home products.

4. Lead architecture, engineering of NLP-based summarization platform (abstract, extractive) for text, audio data, instance & semantic segmentation-based auto-tagging utility for video contents.

1. Lead architecture, engineering of novel data platform - StreamFlux with key-driver of data engineering, sciences utilities, and full-stack solutions: data-quality, data warehousing, disaster recovery, job scheduler, auto-feature.

2. Co-lead in production engineering of mission-critical solutions deliveries, post-production engineering support for early identification, resolution of critical bugs, metrics. Engineered novel product metrics for new feature development, optimization with both open-source, commercial tools in the Apache, Snowflake, & Databricks ecosystems.

3. Actively collaborated with business in driving sales engineering across Americas, Europe. Frequently recognized as a star-contributor in the development team and awarded several additional responsibilities, promotions. Enriched exposure in full-stack data science product engineering, management.

Concentration: Distributed Systems, Wireless Computing and Internet of Things

Relevant Coursework: Core Computer Sciences (Electives: Computer Networks, Software Engineering, HCI), Core Electronics (Electives: Embedded Systems, VLSI Design, Wireless Communication, Advanced Hardware Design).