Summary
I have 16+ years of experience working on biological neural networks as a Neuroscientist at Oxford and UCL as well as industry experience working on applied AI at Amazon Alexa AI (USA), Swiggy, Docsumo and recently as an independent AI consultant. 

I have worked on AI use cases such as Speech Recognition, Content Moderation using NLP, Call Centre Automation, Chatbots, Document AI, Synthetic data, Translation using state-of-the-art AI models such as Transformers, BERT, RoBERTa as well as Large Language Models like GPT4, Claude Sonnet 3.5, Llama 3.1 etc.

As an AI Consultant, I primarily work with large companies including startups and enterprises based in both India and abroad (USA/UK/Europe). I share my AI expertise to guide the in-house AI/Tech teams comprised of Product & Business Leaders, Data Scientists and ML Engineers to plan, strategise, build, improve and deploy AI applications with proven business ROI and customer impact. With my consulting, organisations have saved significant man-hours and costs and developed internal technologies as well as launched customer-facing AI applications.
​I like to share my learnings based on consulting my clients on AI technologies and use cases. Here is a recent selection:
AI Services
​​👉 If you need AI Consulting, Corporate Training, Content, Coaching, Speaking services, call or email me [email protected]
Consulting
I usually work directly with AI/Engineering/Product leaders & their teams who are planning to launch AI use cases to production and help them in various ways:
  • Identification of impactful AI use cases for the relevant domain and industry e.g. e-Commerce, FinTech, Manufacturing etc.
  • Reviewing of internal data assets to validate the feasibility, utility and business impact of the use case
  • Implementation of the Strategy and Roadmap to build the AI solution for the particular use case
  • Prioritisation of the multiple steps involved in experimentation, development and deployment of the final solution
  • Organisational training in specific AI tools and technologies required to build the AI solution
  • Hiring and Mentoring of Data Scientists and Machine Learning Engineers as well as AI Team/Org development
  • Strategy for monitoring and continuous training and active learning from real-world data to ensure high performance
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Here are some examples of the AI problems I have previously solved for my clients:
  • LLMs for B2B E-Commerce use cases 
  • Fine Tuning LLMs for Domain-specific use cases for Enterprises
  • LLM Selection and Evaluation for AI Startups
  • Generative AI Pricing and Monetisation for AI/SaaS startups
  • ​Machine Learning Tools & Infrastructure for Tech Startups
  • Data engineering strategy for D2C E-Commerce startups
  • AI B2B Content Marketing Strategy for AI/SaaS Startups
  • AI & Data Science team building strategy
  • AI team development and upskilling ​​
Corporate Training
  • ​My teaching and corporate training is aimed at both Technical and Business professional and leaders based on my extensive experience in organisations building AI products and leading AI teams in different domains and scale: 
    • Amazon Alexa (Consumer; 500M+ users); Swiggy (B2C E-Commerce); Docsumo (B2B; Enterprise & Mid-market clients)
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  • I conduct curated training programs (virtual as well as on-site) on Predictive & Generative AI Product development, Case studies and Organisational Strategy related to identification and implementation of business-critical AI use cases.​

  • I also provide training on Hiring an AI Team, Professional Career Development and Organisational Upskilling in AI technologies
Content
How do we work together?
  • Please share your proposal detailing your content requirements; timelines; target audience; title, outline, and length of each article; key words/phrases from an SEO perspective; reference articles as well as details of the review & publication process.
  • I typically consider long-term engagements of 3+ months or a minimum of 5 blogs. 
  • I will review your proposal and we discuss and agree on terms of engagement.
  • I will share the draft of each blog and work with your team to incorporate your feedback and prepare the blog for publication on your company's website. 

What topics do I write about?
  • Generative AI, Large Language Models, LLMs as Judge, Vector database, LLM selection, LLM Strategy, use cases etc.
  • Deep Learning, Natural Language Processing, Speech recognition
  • Data Governance, Data Culture, Data Quality and Strategy
  • Deep dive on AI use cases such as Fake News, Image Recognition etc.
  • AI team building and hiring, deep dive on roles and career development

What kind of clients have I worked with?
I have worked with numerous early-stage and growth-stage AI & SaaS startups including: Neptune.ai, Singelstore, Domino Data Labs, Octo.ai, Encord, Atla AI, Pachyderm, Label Studio, Toptal, Fingerprint, OpenLayer, Ikigai Labs etc.

Where can you read my blogs?
You can read a selection of blogs that I've authored for various clients on my blog.
Coaching
Are you currently in one of these situations?
  • Seeking Data Scientist, Applied Scientist, ML Engineer, Research Scientist roles?
  • Struggling to crack AI/ML Technical, System Design interviews?
  • Unable to provide detailed anecdotes for behavioral interviews?
  • ​Looking for personalised mock interviews specific to your role and company?
  • Seeking 1:1 guidance for the overall job interview preparation process?

Testimonials
I have coached 100+ candidates and helped them crack AI/ML roles (Data Scientist, Applied Scientist, Research Scientist) at top technology companies in the USA, including: Apple, Meta, Amazon, LinkedIn, ​Databricks, Twitter. Check out their testimonials.

Career Advice
I like to share my perspective on various topics related to careers in AI including upskilling, deciding what projects to work, which teams/companies to work at, best practices for excelling in your AI/ML jobs etc. You can see my career advice blogs here.
Speaking
  • I am available as a Keynote speaker for in-person or virtual engagements for your AI event. Share the details of your proposed talk (title, duration, audience, format etc.), event, dates, schedule, logistics etc. 

  • I have extensive experience of Public Speaking having delivered 50+ talks on AI & Neuroscience at international conferences (USA, Canada, UK, Germany, Switzerland, France etc.), universities, startups, enterprises, business schools, venture capital firms, online workshops, meet-ups etc. to audiences of varying sizes from 20 to 300+!
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  • You can find a selection of my talks and slides here.
AI Experience
Document AI at Docsumo
At Docsumo, I head a team of 25+ ML and Data engineers to build a Document AI platform using NLP, LLMs, Computer vision:
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  • State-of-the-art Transformer-based deep learning models and LLMs like GPT to extract information from structured and unstructured documents like invoices, bank statements, receipts, tax forms, insurance forms etc.
  • Synthetic Data pipeline to augment training data resulting in significant improvement in performance of above models
  • Chat with Documents powered by GPT-based models
  • Data Annotation operations - tracking and visibility of key metrics like accuracy, velocity and reviews
  • Table detection using classical ML models and structure recognition using deep learning models
  • Quarterly OKR planning for the entire ML org
  • Hiring of ML engineers and scientists
  • ML Team mentorship via regular team and 1:1 meetings
  • Business Strategy for the Intelligent Document Processing market
  • Industry engagement with US customers and SaaS VC firms in India
  • AI Stack: Transformer, BERT, LayoutLM, Large Language models like ChatGPT, GPT3.5+, open-source LMs like Llama2, Dolly; Python, PyTorch, Data augmentation, Synthetic Data, Data Annotation, Data Platform, ML Platform, Table detection and structure recognition, Vector database, Document embeddings, Chat with Documents
AI Research at Amazon Alexa AI
At Amazon Alexa AI, I worked on advancing Alexa's Speech Recognition and Natural Language Understanding AI capabilities.
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  • Developed state-of-the-art end-to-end sequence-to-sequence deep learning models for speech recognition
  • Trained Speech recognition deep learning models on 20000+ hours of data using distributed multi-host, multi-GPU training
  • Deployed high impact Deep learning NLP models deep learning models to detect offensive conversations between users and Alexa in multiple languages using Neural Machine Translation and Synthetic Data generation.
  • Mentored software engineers and interns on machine learning and deep learning
  • Founded Alexa AI blog followed by the Alexa leadership as well as 1500+ scientists & engineers across Alexa, AWS & Amazon
  • Contributed to 'Dive into Deep Learning' book
  • Published a paper at the Amazon Machine Learning Conference on detection of offensive and sensitive content in user interactions with Alexa in multiple languages 
  • Conducted research on homomorphic encryption, federated learning and privacy-preserving deep learning 
  • AI Stack: Transformer, BERT, Seq2Seq, AWS, EC2, CUDA, Python, Bash, Vim, Linux, Docker, TensorFlow, MXNet, NMT, AWS Translate, Sockeye, PyTorch, Fairseq, Tensor2Tensor, Data augmentation, Synthetic Text, Backtranslation
Applied AI at Swiggy
​​​I led the AI Team at Swiggy, India’s largest food ordering and delivery platform where I developed novel Deep Learning technologies for multiple NLP and Speech use cases like Chatbot, Intent recognition, Product Classification, Sentiment analysis of user reviews, Speech recognition for Hinglish customer service conversations, Voice sentiment analysis amongst others.
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  • Managed cross-functional stakeholders across Product, Engineering, Business and Analytics teams and also defined, led and managed POCs with external startups and vendors.
  • Led Swiggy's first ever AI paper on Speech and Language Recognition accepted at INTERSPEECH2020 
  • Led team to win 2nd place in Microsoft's Challenge on 'Speech Technologies for Code-Mixing in Multilingual Communities' 
  • I led the AI team on a paper on identification of bad food quality descriptors in customer chat, at CODS-COMAD 2021​
  • ​NLU modeling using weak supervision to decode intent in code-mixed chat
  • Sentiment analysis to identify negative feelings, emotions and opinions in chat 
  • Language identification in code-mixed chat 
  • Predicting Social Media Escalations based on chat input
  • Classification of Products into multiple categories based on text inputs
  • Named Entity Recognition of various entities in chat conversations
  • AI Stack: Transformer, BERT, RoBERTa, DeepSpeech, AWS, EC2, s3, SageMaker, Python, Jupyter, Bash, Vim, Linux, Docker, TensorFlow, PyTorch, Snowflake
Papers

Gupta A, Sukumaran R, John K, Teki S (2021)
Hostility Detection and Covid-19 Fake News Detection in Social Media
CONSTRAINT Workshop, AAAI 2021 (non-archival) [link] [conference]

Brahma AK, Potluri P, Kanapaneni M, Prabhu S, Teki S (2021)
Identification of Food Quality Descriptors in Customer Chat Conversations using Named Entity Recognition 
CODS-COMAD 2021 Research Track. [link] ​​

​Vijjali R, Potluri P, Iyer S, Teki S (2020)
Two Stage Transformer model for Covid-19 Fake News Detection and Fact Checking
NLP for Internet Freedom Workshop co-located at COLING 2020 [link] [data] [conference] [video summary]

​Rangan P*, Teki S* (2020) [*Equal contribution as first authors]
Exploiting Spectral Augmentation for Code-Switched Spoken Language Identification
1st Workshop on Spoken Language Technologies for Multilingual Communities, INTERSPEECH 2020 [link]

Teki S (2019)
Internationalization of NLP Models for Sensitive Content Detection in Alexa Utterances
Amazon Machine Learning Conference ​
Blogs
​AI: Leadership & Best Practices
​   AI: Data & Governance
​  AI: Use cases
​  Team development