Gagik Amirkhanyan

ML Engineer

https://talent.gravityer.com/gagik-amirkhanyan

Tech Lead, Staff ML Engineer at Google

Google

Key Strengths

Extensive experience in Machine Learning and Deep Learning, particularly with LLMs, Transformers, and MoE architectures at Google.
Strong background in various ML domains including Recommender Systems, Computer Vision, NLP, and Reinforcement Learning.
Proven track record in large-scale ML pre-training and post-training (SFT, Distillation, RL, GRPO, PPO).
Experience with key ML frameworks and libraries such as TensorFlow, Jax, PyTorch, and Numpy.
PhD in Mathematics from Georgia Institute of Technology, indicating strong analytical and problem-solving skills.
Experience at top-tier tech companies (Google, Amazon, Nutanix) in ML-focused roles.
Demonstrated ability to apply ML solutions to real-world problems like time series analysis, anomaly detection, and root cause analysis in distributed systems.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's career trajectory, moving from general software development to specialized ML engineering roles at prominent companies like Amazon and Google, demonstrates adaptability and a drive for continuous learning. The diversity of ML projects (LLMs, CV, NLP, RL, Recommender Systems, time series analysis) indicates a broad interest and ability to contribute to various initiatives, aligning well with dynamic, innovation-driven cultures. The long tenure at Google as an ML Engineer/Tech Lead suggests stability and commitment.

Soft Skills & Operational Fit

The candidate's extensive experience at leading tech companies suggests strong operational fit and ability to work in high-performance environments. The PhD in Mathematics implies strong analytical rigor and problem-solving capabilities. While direct soft skill assessment data is not provided, the progression into a Tech Lead role at Google indicates leadership and collaboration potential.

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Experience

Google

ML Engineer / Tech Lead

August 1, 2019 – Present

Greater Seattle Area · On-site

Nutanix

ML software engineer

April 1, 2018 – August 1, 2019

Greater Seattle Area

Amazon

Machine Learning Software Engineer

February 1, 2017 – April 1, 2018

Greater Seattle Area

Amazon

Software Development Engineer

June 1, 2014 – February 1, 2017

Greater Seattle Area

Macadamian Technologies

Software Developer

October 1, 2007 – May 1, 2010

CQG

Software Developer

November 1, 2005 – June 1, 2007

Unicad

Software Engineer

June 1, 2004 – April 1, 2005

Yerevan, Armenia

Key Strengths

Extensive experience in Machine Learning and Deep Learning, particularly with LLMs, Transformers, and MoE architectures at Google.
Strong background in various ML domains including Recommender Systems, Computer Vision, NLP, and Reinforcement Learning.
Proven track record in large-scale ML pre-training and post-training (SFT, Distillation, RL, GRPO, PPO).
Experience with key ML frameworks and libraries such as TensorFlow, Jax, PyTorch, and Numpy.
PhD in Mathematics from Georgia Institute of Technology, indicating strong analytical and problem-solving skills.
Experience at top-tier tech companies (Google, Amazon, Nutanix) in ML-focused roles.
Demonstrated ability to apply ML solutions to real-world problems like time series analysis, anomaly detection, and root cause analysis in distributed systems.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Gagik Amirkhanyan

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Education

Experience

Key Strengths

Cultural & Operational Fit