Anirudh Sridhar

Machine Learning Engineer

Bengaluru, Karnataka, India4 yrs 5 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in MLOps with extensive tool integration experience.
Proven track record in enhancing CI/CD pipelines.
Strong foundation in computer science with a focus on AI.

Stackforce AI infers this person is a Machine Learning Engineer specializing in MLOps within the SaaS industry.

Contact

Skills

Core Skills

MlopsMachine LearningCi/cdComputer Vision

Other Skills

AWSAirflowAmazon BedrockApache KafkaArtificial Intelligence (AI)AutogenAzure Open AIBlue PrismC++Computer ScienceContinuous Integration and Continuous Delivery (CI/CD)Data AnalysisData AnalyticsData CleaningData Science

About

I am a passionate Machine Learning Engineer specializing in MLOps, where I excel at the convergence of machine learning and operational efficiency. With extensive experience in utilizing advanced tools like SageMaker, Kubeflow, Airflow, and MLflow, I have effectively developed and optimized machine learning platforms that deliver substantial business value. My expertise in Terraform on cloud platforms like AWS, along with enhancing monitoring capabilities through Grafana, highlights my dedication to operational excellence. Throughout my career, I have played a pivotal role in advancing CI/CD pipelines, automating resource management, and developing robust APIs for model inference. My commitment to innovation is evident in projects like the Telecom Churn Prediction ETL and ML pipeline, as well as LLM-based RAG pipelines, where I have demonstrated my ability to manage large data volumes and implement low-latency solutions. With a solid foundation in computer science and a keen interest in emerging technologies, I am eager to contribute to forward-thinking teams that prioritize data-driven decision-making and continuous advancement in AI systems.

Experience

4 yrs 5 mos

Total Experience

1 yr 1 mo

Average Tenure

1 yr 11 mos

Current Experience

New relic

Machine Learning Engineer

Jul 2024 – Present · 1 yr 11 mos · Bengaluru, Karnataka, India · Hybrid

Explored and integrated SageMaker, Kubeflow, Airflow, and MLflow to build a robust machine learning platform.
Developed an evaluation pipeline using Airflow to select the best model, log hyperparameters, and error rates in MLflow.
Created a training pipeline to update, deploy, and register the best model in MLflow, along with an inference API for predictions.
Developed a Data Retriever agent with both streaming and non-streaming APIs, and implemented an asynchronous workflow that is triggered by alerts on any metric using an SQS + Lambda combination, seamlessly integrating the system with Slack for notifications.
Worked on building internal LLM and RAG evaluation pipeline using airflow
Worked on Knowledge-Augmented Generation, an enhancement over the existing Retrieval-Augmented Generation (RAG) system.
Working on hosting a Small Language Model using VLLM

SageMakerKubeflowAirflowMLflowTerraformAWS+3

Outsystems

Machine Learning Engineer

Jul 2023 – Jul 2024 · 1 yr · Bengaluru, Karnataka, India · Hybrid

Explored Flyte as an orchestrator and deployed it on the EKS cluster using Terraform
Added alerts in Grafana dashboards to enhance monitoring capabilities.
Contributed to the expansion of CI/CD pipelines by incorporating additional stages.
Developed Terraform scripts to automate the creation of S3 buckets.
Added a middleware in the platform to store requests and responses in the data lakes which can be used for RLHF.
Worked on building LLM Gateway which helps research scientists connect to multiple LLM providers with the same endpoint.

FlyteEKSTerraformGrafanaCI/CDMLOps

Mad street den

3 roles

Junior Machine Learning Engineer

May 2023 – Jun 2023 · 1 mo · Chennai, Tamil Nadu, India · Remote

Worked on generating handwritten and computerized documents for training of inhouse OCR
Worked on creating synthetic watermark, text and logo data for retraining model

Machine Learning Trainee

Jul 2022 – Apr 2023 · 9 mos · Chennai, Tamil Nadu, India · Remote

Worked on improving the computer vision model accuracy on client data from 80% to 95% which helped in the company's growth
Used pyspark to fetch client data from delta table and use that data to improve models, dockerize it, create graphs, deploy it at scale and monitor the traffic in kibana
Applied heuristics and OCR techniques for generating text tags

Computer VisionPysparkDocker

Machine Learning Intern

Feb 2022 – Jun 2022 · 4 mos · Chennai, Tamil Nadu, India · Remote

Worked on the images of side, front, lower and upper views of teeth and predicted if aligners could be applied or not

Ab inbev india

RPA Intern

Aug 2021 – Jan 2022 · 5 mos

Worked on Automating SAP Process to end or extend an employee's assignment and the process of downloading bank statements for Wells Fargo Bank which provided a benefit of 0.5 FTE i.e saving 960 hrs of manpower in a year.