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 prototyp - esUnderstanding business objectives and developing models that help to achieve them, along with metrics to track their progre
- ssDesign ML applicatio
- nsSelect appropriate annotated datasets for Supervised Learning metho
- dsAnalysing the ML algorithms that could be used to solve a given problem and ranking them by their success probabili
- tyExploring 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 wor
- ldVerifying data quality, and/or ensuring it via data cleani
- ngSupervising the data acquisition process if more data is need
- edFinding available datasets online that could be used for traini
- ngDefining validation strategi
- esDefining the pre-processing or feature engineering to be done on a given datas
- etDefining data augmentation pipelin
- esTraining models and tuning their hyperparamete
- rsRun evaluation experimen
- tsPerform statistical analysis of results and refine mode
- lsAnalysing the errors of the model and designing strategies to overcome th
- emDeploying models to producti
- onRemain updated in the rapidly changing field of machine learni
ng
Requiremen
- ts:
Proven experience as an AI/ML Engineer or similar - roleAbility to effectively design software architec
- tureStrong knowledge of Python, a
- nd RDeep knowledge of math, probability, statistics, and algori
- thmsAbility to write robust and testable
- codeExperience with machine learning frameworks (like Keras, PyTorch, TensorFlow) and libraries (like scikit-learn, pandas, spacy, N
- LTK)Good to have knowledge of Amazon and Google ML serv
- icesGood to have knowledge of Docker and Kubernetes and cloud platforms like AWS, A
- zureGood to have knowledge of ML Ops pipelines working to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of AI/ML mod
- els.Experience communicating research findings and analysis in both written and spo
- ken.An analytical mind with problem-solving abili
- tiesExcellent communication sk
- illsAbility to work in a t
eam.
Qualifica
- tion:
B.S. Or M.S. in Computer Science or equivalent exper
ience.
