ClearScale is a leading cloud systems integration company and AWS Premier Consulting Partner providing a wide range of cloud services including: cloud consulting, architecture design, migration, automation, application development, and managed services.
We help Fortune 500 enterprises, mid-sized business, and startups in verticals like: Healthcare, Education, Financial Services, Security, Media and Technology succeed with ambitious, challenging, and unique cloud projects. We architect, develop, and launch innovative and sophisticated solutions using the best cutting-edge cloud technologies.
ClearScale is growing quickly and there is high demand for the services we provide. Clients come to us for our deep experience with Big Data, Containerization, Serverless Infrastructure, Microservices, IoT, Machine Learning, DevOps and more.
ClearScale is looking for an experienced Machine Learning Engineer to participate in a custom data pipeline development project.
Responsibilities:
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Select and justify the appropriate ML approach for a given business problem
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Design and implement scalable, cost-optimized, reliable, and secure ML solutions
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The ability to express the intuition behind basic ML algorithms
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Create data repositories for machine learning
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Identify and implement a data-ingestion solution
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Identify and implement a data-transformation solution
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Sanitize and prepare data for modeling
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Perform feature engineering (missing and unbalanced data, outliers)
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Analyze and visualize data for machine learning
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Train machine learning models
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Perform model tuning (learning rate, regularization techniques), hyperparameter optimization
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Evaluate machine learning models
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Deploy and operationalize machine learning solutions
Basic Qualifications
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Hands-on experience a variety of other AWS ML tools, especially Glue ML Transform
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Hands-on experience with non AWS ML tools implemented in an AWS Environment
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Bachelor or Specialist/Masters in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
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2+ years of experience in Machine Learning/Data Science applications (classical and deep learning models, ensemble learning)
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2+ years of experience in Python ML frameworks (NumPy, SciPy, scikit_learn, Pandas, Jupyter, Matplotlib)
Preferred Qualifications
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Knowledge of ANSI SQL (ability to write advanced analytical queries)
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In-depth knowledge in one or more Machine Learning areas: Deep Learning, NLP, Recommender Systems, Reinforcement Learning
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In-depth knowledge of Tensorflow/Keras
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In-depth knowledge of AWS SageMaker and one or more of the following related algorithms: Linear Learner, XGBoost, Seq2Seq, DeepAR, BlazingText, Object2Vec, Object Detection, Image Classification, Semantic Segmentation, Random Cut Forest, Neural Topic Model, Latent Dirichlet Allocation, K-Nearest-Neighbors, K-Means, Principal Component Analysis, Factorization Machines, IP Insights, Reinforcement Learning, Automated Model Tuning
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In-depth knowledge of one or more of the following AWS technologies: S3, Kinesis, Glue, Redshift, RDS, Aurora, DynamoDB, ElastiCache, Data Pipeline, Batch, DMS, Step Functions, Athena, QuickSight, EMR, SageMaker, Ground Truth, Comprehend, Translate, Transcribe, Polly, Rekognition, Forecast, Lex, Personalize, Textract, DeepRacer, DeepLens, IoT
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Hands-on experience with Apache Spark MLLib (Zeppelin)
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Hands-on experience with OpenCV
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Hands-on experience with advanced Python data frameworks (Seaborn, PyTorch, Dask)
What’s in it for you?
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Competitive Salary; Benefits
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Paid Time Off
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Opportunity to build a leadership career in the fast-growing Cloud industry with an industry leader.
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Collaborative, high-energy culture
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100% distributed workforce - everyone works from home!
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Learning opportunities
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