With the exponential rise of artificial intelligence, almost all the organisations are building AI and ML capabilities in the analytics tech stack. With the current shift in technological In this article, Analytics India Magazine offers you five current openings on machine learning engineer to apply for.
- Have a Bachelors or Masters degree in Computer Science with 5-9 years of experience in Machine Learning (Statistical pattern recognition, semi-supervised and unsupervised learning, statistical modeling, etc.)
- Hands on development experience in Java, good to have experience of using Scala-Spark
- Experience with a statistical package such as R or Python, etc.
- Strong computer science fundamentals in algorithms and data structure
- Ability/Openness to work as a full stack engineer
- Knowledge of Machine Learning concepts (Generalized Linear models, Regularization, Random Forest, Time Series models, etc.)
- Strong written and verbal communication skills
- Experience with large data sets and distributed computing (Hive/Hadoop/Spark) a plus.
- Ability to take a problem, analyze, design, educate team members on it and work with them to solve the problem with high quality and on time.
- Design and implement ML applications.
- Work with large amounts of structured and unstructured data.
- Design and develop high-quality, production-ready code in java or Scala-spark that can be used by thousands of users of our cloud platform.
- Share your Machine learning expertise to coach junior team members interested in this domain.
- Participate in architectural initiatives, balancing long-term platform velocity with short-term customer needs.
- Work closely with cross-functional teams across geographies.
- Commitment to proper software engineering practices – design, testing, documentation, code reviews, agile, etc.
Click here to apply
2| ML Engineer At Rede Consulting Services
- The Machine Learning Engineer must have industry experience working on a range of classification and optimization problems, e.g. payment fraud, click-through rate prediction, click-fraud detection, search ranking, text/sentiment classification, collaborative filtering, recommendation, and spam detection
- The candidate must have 2+ years of experience in one or more of the following areas like machine-learning algorithms, NLP, recommendation-systems, pattern-recognition, data-mining or artificial intelligence
- The candidate must have experience in programming in any of the languages such as Python, Java, C/C++, Scala, Clojure, Go, R and Machine-Learning tools like Apache Spark, Google Tensorflow, Moses, Phrasal, NLTK, GATE, SRILM, Tagger, CoreNLP, etc.
- Optimization Search-Ranking
- Click-Through-Rate-Prediction Machine Learning
Click here to apply
Prerequisites & Responsibilities:
- Expert in Natural Language Processing (NLP) to understand user questions, analyze intent to find answers from customers structured data set.
- Experience using NLP software libraries (e.g., Python NLTK, QUEPY)
- Experience in one of the ML libraries like Scikit Learn/Pandas/Tensorflow.
- 4 to 5 years of experience.
- Communications skill is one of the keys
- Should be able to work independently
- Should be able to work under tight deadlines
- Experience working with Overseas especially US customers is needed
Click here to apply
This role is for a Machine Learning Data Engineer to join the Analytics and Artificial Intelligence team. The focus of the team is to innovative algorithms and models that make intelligent, automated, decisions in real time to make engineering process better, faster and accurate.
- 3-5 years of experience in Data Warehousing with Big Data or Cloud
- Graduate degree educated in computer science or a relevant subject
- Good software engineering principals
- Knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce is desirable but not essential
- Strong coding skills in Python.
- Deep knowledge of testing frameworks and libraries
- Working knowledge of the pros, cons, and usages of various ML/DL applications (such as Keras, Tensorflow, Python sci-kit learn and R)
- Experience of working in Agile delivery
- Good knowledge of database management languages e.g. SQL, PostgreSQL.
- Knowledge and practical experience of cloud-based platforms and their ML/DL offerings (such as Google GCP, AWS, and Azure) would be advantageous
- Understanding of infrastructure (including hosting, container-based deployments and storage architectures) would be advantageous
- You will be responsible for implementing ML models in the production type environment
- You will be responsible for creating reusable and scalable data pipelines
- You will be responsible for reverse engineering Python scripts and notebooks
- You will be responsible for scaling up algorithms in a big data environment
- You will be responsible for turning experimental ML pipelines into resilient production grade code
- You will be responsible for extracting re-usable code to generic libraries and ML workflows
- Work closely with Data Scientists and Data Engineers to productionise and deploy machine learning models
- Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines
- Play an active role in leading team meetings and workshops with clients.
- Choose and use the right analytical libraries, programming languages, and frameworks for each task
- Produce high-quality code that allows us to put solutions into production
- Refactor code into reusable libraries, APIs, and tools.
- Help us to shape the next generation of our products.
Click here to apply.
- Master’s Degree or Ph.D. – Computer Science, Artificial Intelligence.
- Hands on Experience in implementing deep learning architectures using the latest machine learning tech and frameworks.
- Existing track record as a researcher in machine learning with the published scientific journal.
- Design and build novel machine learning models to solve unique medical problems and improve patient outcomes.
- Test and evaluate algorithms on large medical datasets to prove the robustness
- Deliver high quality and production-ready code
- Desirable Skills
- Solid Python and C++ experience and Linux user.
- Solid mathematical background.
- Experience with a vast set of computer vision libraries.
- Deep understanding and hands-on experience in state-of-the-art Medical Image Analysis algorithms will be a plus.
Click here to apply
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