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Ojasvi **** AI Consultant

$720 / day

Summary

Results-oriented AI Consultant with extensive experience in machine learning, computer vision, and data science, specialising in advanced algorithms, model optimisation, and high-performance computing. Proven ability to enhance particle detection in cryoEM samples and develop MLOps systems that drive significant revenue growth and operational efficiency. Skilled in deploying NLP-based solutions, including sentiment analysis and bias detection, with a strong background in consulting and developing innovative AI frameworks. Passionate robotics instructor and published researcher with a solid academic foundation in Data Science, adept at utilising diverse tools and frameworks to deliver impactful data-driven insights.

SKills

AirflowAnalyticsAWS SageMakerBashBig DataComputer VisionData visualisationDatabase ManagementDeep LearningDockerFlaskGITGitHubHigh Performance ComputingLarge Language ModelsMachine LearningMLOpsNLPPowerBIPredictive ModellingPySparkPythonPyTorchRReportingResponsible AIScikit-LearnSparkSQLTableauTensorFlow
AI ConsultantMachine Learning EngineerNatural Language Processing (NLP) Engineer

Education

2020 Master of Science at Monash University
2018 Bachelor of Technology at NMIMS University

Experience

2023 AI Consultant at Walter and Eliza Hall Institute of Medical Research

– Explored cutting-edge object detection algorithms (DynamicDet, YOLOv7, UNet)
and applied denoising techniques (Topaz, filtering, contrast enhancement) to
improve particle picking in cryoEM protein samples.
– Conducted ablation studies and optimised particle detection, improving model precision
by 0.3 and recall by 0.25.
– Utilised high-performance computing clusters with Bash scripting and command-line
deployment to enhance computer vision applications in PyTorch.

2022 Robotics Instructor at Aerobotics Global

– Passionate robotics instructor teaching Arduino coding and fostering logical thinking in
young learners.

2020 Senior Data Scientist at Mphasis (NextLABS)

– Developed the backend code structure for PACE-ML, including modules for data processing,
training pipelines, performance and fairness metrics, incremental learning,
hyperparameter tuning, and workflow orchestration using Airflow.
– Created machine learning pipelines for home loan application processing, integrating
Responsible and Fair AI solutions that improved pipeline efficiency and increased
revenue by $150k.
– Consulted on and developed an Aspect-Based Sentiment Analysis pipeline for AWS
Marketplace Listings, creating over 20 listings and achieving a 35% increase in
efficiency.
– Contributed to the Organisations Quantum Challenge, developing a Trainable Quantum
Machine Learning algorithm for image classification, which enhanced accuracy by 7%.