Machine learning Engineer

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Basic Responsibilities:● Work on creating high performance and scalable solution architectures for differentproblems● Develop sophisticated yet simple interpretations and communicate insights to clientsthat lead to quantifiable business impact● Ability to envision new technologies and turn them into innovative products.● Remain knowledgeable about current technology and carry out research to identify newtrends that can be used to achieve maximum results● Working with the offshore team to build, test, deploy, and assess models that predictand optimize business outcomes based on client’s success criteria● Carry out other technical related duties that may be required. Be abreast of the bestcoding and architecting practices

Skills Required:● Master’s in Computer Science/Electrical Engineering with focus on AI/ML● Strong publication record, with publications in major machine learning conferences (e.g.NeurIPS, ICLR, ICML, etc.)● Should have at least 3 years of experience with a minimum of 3 years in the design anddevelopment of AI/ML-based systems.● Knowledge of statistical modeling and popular machine learning models.● Hands-on with Python/R programming and knowledge of machine learning tools likeScikit-Learn, Pandas, Tensorflow, Pytorch is a must ● Should possess knowledge of at least one cloud platform (GCP, Azure, or AWS) andmachine learning services offered by them.● Working knowledge of Recommender systems is a must ● Conceptual and code level understanding of Computer Vision, Object detection(FasterRCNN, YOLO, SSD, etc), Image similarity is good to have● NLP: Vector Space modeling in NLP, LSTMs, Sequence modeling, Attention modeling, BERT,Large Language models is a must. Knowledge on using the above-mentioned techniquesperforming Document classification, Semantic similarity, NER, Sentiment Analysis is amust ● Experience in the design and development of continuous delivery and automationpipelines (MLOps) in the cloud is good to have ● Ability to use analytical thinking and business understanding to perform an insightful,actionable quantitative and qualitative analysis of the business● Experience in working in an Agile environment● Strong verbal and written communication skills.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!