Akshat Jindal

AI Researcher

San Francisco, California, United States5 yrs 3 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in Statistical ML, Deep Learning, and NLP.
Achieved 2% revenue gain through innovative ad delivery models.
Research experience at Stanford AI Lab and Facebook.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in AI-driven advertising and data science.

Contact

Skills

Core Skills

Machine LearningDeep LearningNatural Language Processing (nlp)ResearchGenerative ModellingProbabilistic ModelsTeachingComputer ScienceProgrammingData Mining

Other Skills

AlgorithmsApplied Machine LearningArtificial Intelligence (AI)BashBayesian inferenceBayesian methodsC (Programming Language)Computer VisionData StructuresEnglishFrenchGenerative Adversarial Networks (GANs)GitGraphical ModelsLeadership

About

I'm a recent graduate from Stanford with a Master's in CS (AI/ML specialisation). My core competencies lie in Statistical ML, Deep Learning and NLP and am comfortable working with Python, C++ ; Libraries/Frameworks like Pytorch, Keras, HuggingFace etc. I've worked in Generative Modelling with Stanford AI Lab as a Research Asst (RA), Multilingual Q/A under CS224n among other DL projects at Stanford. Interestingly, I also recently worked on a market research RA to gauge current NLP startup trends in the valley. I interned with the FB Marketplace Ads Delivery team last summer where we trained a Sparse NN model to deliver ads, contextually relevant to the product on Marketplace. I now work full-time at Facebook and aim to work on projects that align with my skillset, involving ML models and services being deployed for high business impact and improving user experience.

Experience

Facebook

2 roles

Machine Learning Engineer

Jul 2021 – Present · 4 yrs 8 mos · Menlo Park, California, United States

Machine LearningDeep Learning

Software Engineer Intern

Jun 2020 – Sep 2020 · 3 mos · Menlo Park, California, United States

Collaborated with the FB Marketplace Ads team to develop models to deliver contextually relevant ads to the users. By using simple neural network architectures , FAISS and experimenting with embedding metrics, we achieved a 2% revenue gain on online experiments!

Neural NetworksData MiningPythonMachine LearningDeep Learning

Stanford university

3 roles

Graduate Research Assistant

Sep 2020 – Jun 2021 · 9 mos · Stanford, CA, United States

Working with the US-Asia Technology Centre to survey SOTA NLP libraries and platforms.

Natural Language Processing (NLP)Research

Graduate Research Assistant

Promoted

Mar 2020 – Jun 2020 · 3 mos

RA at Stanford AI Lab under Prof Stefano Ermon

Generative ModellingResearch

Graduate Teaching Assistant

Jan 2020 – Mar 2020 · 2 mos

Course assistant to Prof Stefano Ermon for CS228 : Probabilistic Graphical Models

Probabilistic ModelsTeaching

Indian institute of technology, kanpur

Undergraduate Teaching Assistant

Jan 2019 – May 2019 · 4 mos · Kanpur

Teaching assistant for the course ESC101, an introduction to programming fundamentals course at IITK.

TeachingComputer Science

Microsoft

Software Engineer Intern

May 2018 – Jul 2018 · 2 mos · Hyderabad Area, India

1. Worked with the Bing relevance team to help improve the relevance of Bing queries.
2. Used data mining principles to filter out germane queries.
3. Achieved relevance improvement of more than 3 points on production.
4. Awarded Best Paper award in Synapse'18(Microsoft's annual AI conference) for the paper I presented based on my internship project.

TeachingProgramming

Pratt & whitney

Data Science Intern

May 2017 – Jul 2017 · 2 mos · Singapore

1. Developed a strategy to reduce the turn around time of the air-engines on the shop floor by 10% by means of collecting and analysing data thus enabling cost reduction and customer delight.
2. Planned and implemented a strategic reallocation of human resource on the shop floor by analysing previous year's data.

Data MiningMachine Learning