Machine Learning Researcher and Engineer

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Description

FastAPI Kafka Elasticsearch Kubernetes C++ GCP Flask Kubeflow Langchain Scala C Mlflow NLTK Docker PyTorch PostgreSQL Llamaindex PyFlink Ray OpenCV Grafana Azure Neo4j Ansible Keras AWS Triton Spark MySQL Python GraphQL Bash Terraform Openshift Spacy TigerGraph Tensorflow

I'm on the job market and open to roles in industry! With over six years of experience in applied machine learning, I worked mainly on pipelining machine learning models for search retrieval, ranking (text, image, multimodal), recommender systems, including some computer vision tasks (object detection, segmentation) mainly from ECCV, CVPR, NeurIPS competitions on Kaggle, and experience consulting on the quant side dealing with financial AI use-cases (scenario generation of stock portfolios, fraud detection at scale such as multi-chain Blockchains transactions > 100M). I am amenable to acquiring proficiency in diverse programming languages, frameworks, and infrastructure (currently learning Rust). My problem-solving aptitude extends beyond coding and product development; I actively seek opportunities to enhance the development process and assist colleagues through mentoring and coaching. If your team requires a machine learning researcher, engineer, data scientist, or research scientist to build production-grade modelling pipeline focussed toward performance optimisation and producing high-quality code and features, I am readily available for a full-time, remote, contract, and long-term roles.