Machine Learning Engineers
3 days ago
**Responsibilities**:
- Work in interdisciplinary teams that combine technical, business, and data science competencies.
- Contribute to crafting and running bespoke ML services as per requirements
- Build and improve machine learning and analytics platform and ensure that ML algorithms generate accurate user recommendations.
- Keep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production.
- Provide engineering solutions and framework to support machine learning and data-driven business activities at a large scale.
- Perform R&D on new technologies and solutions to improve accessibility, scalability, efficiency, and usabilities of machine learning and analytics platform.
- Work with data scientists to build end-to-end machine learning and analytics solution to solve business challenges.
- Turn advanced machine learning models created by data scientists into the end-to-end production-grade system.
- Build analytics platform components to support data collection, exploratory, and integration from various sources, being data API, RDBMS, or big data platform.
- Study and evaluate the state-of-the-art technologies, tools, and frameworks of machine learning engineering.
- Contribute to the creation of blueprint and reference architecture for various machine learning use cases.
**Qualifications**:
- 5+ years of end-to-end experience in designing and implementing large scale ML solutions/services
- Hands-on experience in machine/deep learning techniques (TensorFlow, Keras, Theano, MXNet, Microsoft DMTK etc.)
- Hands-on experience with big data stacks (Spark, Hadoop, Storm, Hive & Pig) and NoSQL stores
- Solid understanding of Advanced math skills (linear algebra, Bayesian statistics, group theory) and statistics
- Proficient in Spark Core, Spark-SQL, Scala-Programming, and Streaming datasets in Big Data platform
- Skilled in Machine Learning Algorithms and Libraries
- High proficiency in Python, R, Scala, or Java programming
- Excellent understanding of technology life cycles and the concepts and practices required to build big data solutions
- Cloud development experience (AWS, GCP / Azure)
- Good understanding of DevOps and Agile way of working
- Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
**Professional Skills**:
- Eagerness to contribute in a team-oriented environment
- Ability to work creatively and analytically in a problem-solving environment
- Desire to work in an information systems environment
- Excellent leadership, communication (written and oral) and interpersonal skills
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