We are looking for a Senior Data Scientist to help us improve our Data Science products and create new applications. AI/ML Engineer responsibilities include designing and developing machine learning and deep learning systems. Running machine learning tests and experiments and implementing appropriate ML algorithms. To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods, and programming. You will be responsible for developing efficient self-learning ML applications.
Responsibilities
:
Study and transform data science prototypes
Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
Design ML applications
Select appropriate annotated datasets for Supervised Learning methods
Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Finding available datasets online that could be used for training
Defining validation strategies
Defining the preprocessing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyperparameters
Run evaluation experiments
Perform statistical analysis of results and refine models
Analyzing the errors of the model and designing strategies to overcome them
Deploying models to production
Remain updated in the rapidly changing field of machine learning
Requirements
:
Proven experience as an AI/ML Engineer or similar role
Ability to effectively design software architecture
Strong knowledge of Python, and R
Deep knowledge of math, probability, statistics, and algorithms
Ability to write robust and testable code
Experience with machine learning frameworks (like Keras, PyTorch, Tensorflow) and libraries (like scikit-learn, pandas, spacy, NLTK)
Good to have knowledge of Amazon and Google ML services
Good to have knowledge of Docker and Kubernetes and cloud platforms like AWS, Azure
Good to have knowledge of MLOps pipelines working to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of AI/ML models.
Experience communicating research findings and analysis in both written and spoken.
An analytical mind with problem-solving abilities
Excellent communication skills
Ability to work in a team.
Qualification
:
B.S. Or M.S. in Computer Science or equivalent experience.
