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 prototype
- sUnderstanding business objectives and developing models that help to achieve them, along with metrics to track their progres
- sDesign ML application
- sSelect appropriate annotated datasets for Supervised Learning method
- sAnalyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probabilit
- yExploring 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 worl
- dVerifying data quality, and/or ensuring it via data cleanin
- gSupervising the data acquisition process if more data is neede
- dFinding available datasets online that could be used for trainin
- gDefining validation strategie
- sDefining the pre-processing or feature engineering to be done on a given datase
- tDefining data augmentation pipeline
- sTraining models and tuning their hyperparameter
- sRun evaluation experiment
- sPerform statistical analysis of results and refine model
- sAnalysing the errors of the model and designing strategies to overcome the
- mDeploying models to productio
- nRemain updated in the rapidly changing field of machine learnin
g
Requirement
- s:Proven experience as an AI/ML Engineer or similar ro
- leAbility to effectively design software architectu
- reStrong knowledge of Python, and
- RDeep knowledge of math, probability, statistics, and algorith
- msAbility to write robust and testable co
- deExperience with machine learning frameworks (like Keras, PyTorch, Tensorflow) and libraries (like scikit-learn, pandas, spacy, NLT
- K)Good to have knowledge of Amazon and Google ML servic
- esGood to have knowledge of Docker and Kubernetes and cloud platforms like AWS, Azu
- reGood to have knowledge of MLOps pipelines working to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of AI/ML model
- s.Experience communicating research findings and analysis in both written and spoke
- n.An analytical mind with problem-solving abiliti
- esExcellent communication skil
- lsAbility to work in a tea
m.
Qualificati
- on:B.S. Or M.S. in Computer Science or equivalent experien
ce.
