- Perform research and development on Machine Learning specifically in the areas of Speech Recognition, Digital signal processing, audio signal processing, NaturalLanguage processing, Natural Language Understanding
- Read and keep up with the research in Speech recognition, Machine Learning, Deep
- Understand and implement research papers to the business problem and build the
- Contribute to applied research and open source community
- Mentor and guide team members
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About TensorIoT
TensorIoT is an AWS Advanced Consulting Partner. We help companies realize the value and efficiency of the AWS ecosystem. From building PoCs and MVPs to production-ready applications, we are tackling complex business problems every day and developing solutions to drive customer success.
TensorIoT's founders helped build world-class IoT and AI platforms at AWS and Google and are now creating solutions to simplify the way enterprises incorporate edge devices and their data into their day-to-day operations. Our mission is to help connect devices and make them intelligent. Our founders firmly believe in the transformative potential of smarter devices to enhance our quality of life, and we're just getting started!
TensorIoT is proud to be an equal-opportunity employer. This means that we are committed to diversity and inclusion and encourage people from all backgrounds to apply. We do not tolerate discrimination or harassment of any kind, and make our hiring decisions based solely on qualifications, merit, and business needs at the time.
You have:
- Study and transform data science prototypes.
- Research and implement appropriate ML algorithms and tools.
- Data exploratory analysis
- Feature engineering
- Implement basic ETL pipelines with database/data lake tools
- Conduct scientific research on the latest technologies and ML models
- Run machine-learning tests and experiments.
- Perform statistical analysis and fine-tuning using test results.
- Extend existing ML libraries and frameworks.
- Present scientific research methodologies to the audience
Machine Learning Engineer responsibilities include:
- Designing and developing machine learning and deep learning systems
- Running machine learning tests and experiments
- Implementing appropriate ML algorithms
Must have/Requirements.
· Proven experience as a Machine Learning Engineer or similar role
· Must have experience with integrating applications and platforms with cloud technologies (i.e., AWS)
· Docker containers knowledge
· Know about distributed training tools
· Experience with GPU acceleration (i.e., CUDA and cuDNN)
· Create feature engineering pipelines to process high-volume, multi-dimensional, unstructured (audio, video, NLP) data at scale.
· Knowledge of server-less architectures (e.g., Lambda, Kinesis, Glue).
· Understanding of end-to-end ML project lifecycle.
· Must have experience with Data Science tools and frameworks (i.e., Python, Scikit, NLTK, NumPy, Pandas, TensorFlow, Kera’s, R, Spark, PyTorch).
· Experience with cloud-native technologies, microservices design, and REST APIs.
· Knowledge of data query and data processing tools (i.e., SQL)
· Deep knowledge of Math, Probability, Statistics, and Algorithms
· Strong understanding of image recognition & computer vision.
· Must have 6- 10 years of experience.
· Excellent communication skills
· Ability to work in a team.
· BSc or Master in Computer Science, Mathematics, or a similar field;
· A Ph.D. degree is a plus.
Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.
1+ years of proven experience in ML/AI with Python
Work with the manager through the entire analytical and machine learning model life cycle:
⮚ Define the problem statement
⮚ Build and clean datasets
⮚ Exploratory data analysis
⮚ Feature engineering
⮚ Apply ML algorithms and assess the performance
⮚ Codify for deployment
⮚ Test and troubleshoot the code
⮚ Communicate analysis to stakeholders
Technical Skills
⮚ Proven experience in usage of Python and SQL
⮚ Excellent in programming and statistics
⮚ Working knowledge of tools and utilities - AWS, DevOps with Git, Selenium, Postman, Airflow, PySpark
Job Responsibilities:
- Identify valuable data sources and automate collection processes
- Undertake preprocessing of structured and unstructured data.
- Analyze large amounts of information to discover trends and patterns
- Helping develop reports and analysis.
- Present information using data visualization techniques.
- Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems.
- Evaluating changes and updates to source production systems.
- Develop, implement, and maintain leading-edge analytic systems, taking complicated problems and building simple frameworks
- Providing technical expertise in data storage structures, data mining, and data cleansing.
- Propose solutions and strategies to business challenges
Desired Skills and Experience:
- At least 1 year of experience in Data Analysis
- Complete understanding of Operations Research, Data Modelling, ML, and AI concepts.
- Knowledge of Python is mandatory, familiarity with MySQL, SQL, Scala, Java or C++ is an asset
- Experience using visualization tools (e.g. Jupyter Notebook) and data frameworks (e.g. Hadoop)
- Analytical mind and business acumen
- Strong math skills (e.g. statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills.
- Bachelor’s / Master's Degree in Computer Science, Engineering, Data Science or other quantitative or relevant field is preferred
We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.
Roles and Responsibilities:
- Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
- Develop programs in Scala and Python as part of data cleaning and processing.
- Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.
- Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
- Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
- Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Provide high operational excellence guaranteeing high availability and platform stability.
- Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.
Skills:
- Experience with Big Data pipeline, Big Data analytics, Data warehousing.
- Experience with SQL/No-SQL, schema design and dimensional data modeling.
- Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
- Experience in designing systems that process structured as well as unstructured data at large scale.
- Experience in AWS/Spark/Java/Scala/Python development.
- Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
- Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
- Prior exposure to streaming data sources such as Kafka.
- Should have knowledge on Shell Scripting and Python scripting.
- High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
- Experience with NoSQL databases such as Cassandra / MongoDB.
- Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
- Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
- Experience building and deploying applications on on-premise and cloud-based infrastructure.
- Having a good understanding of machine learning landscape and concepts.
Qualifications and Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.
Certifications:
Good to have at least one of the Certifications listed here:
AZ 900 - Azure Fundamentals
DP 200, DP 201, DP 203, AZ 204 - Data Engineering
AZ 400 - Devops Certification
- 3+ years of experience in Machine Learning
- Bachelors/Masters in Computer Engineering/Science.
- Bachelors/Masters in Engineering/Mathematics/Statistics with sound knowledge of programming and computer concepts.
- 10 and 12th acedemics 70 % & above.
Skills :
- Strong Python/ programming skills
- Good conceptual understanding of Machine Learning/Deep Learning/Natural Language Processing
- Strong verbal and written communication skills.
- Should be able to manage team, meet project deadlines and interface with clients.
- Should be able to work across different domains and quickly ramp up the business processes & flows & translate business problems into the data solutions
- 3-5yrs of practical DS experience working with varied data sets. Working with retail banking is preferred but not necessary.
- Need to be strong in concepts of statistical modelling – particularly looking for practical knowledge learnt from work experience (should be able to give "rule of thumb" answers)
- Strong problem solving skills and the ability to articulate really well.
- Ideally, the data scientist should have interfaced with data engineering and model deployment teams to bring models / solutions to "live" in production.
- Strong working knowledge of python ML stack is very important here.
- Willing to work on diverse range of tasks in building ML related capability on the Corridor Platform as well as client work.
- Someone with strong interest in data engineering aspect of ML is highly preferred, i.e. can play dual role of Data Scientist as well as someone who can code a module on our Corridor Platform writing robust code.
Structured ML techniques for candidates:
- GBM
- XgBoost
- Random Forest
- Neural Net
- Logistic Regression
The Job
The Architect, Machine Learning and Artificial Intelligence including Computer Vision will grow and lead a team of talented Machine Learning (ML), Computer Vision (CV) and Artificial Intelligence (AI) researchers and engineers to develop innovative machine learning algorithms, scalable ML system, and AI applications for Racetrack. This role will be focused on developing and deploying personalization and recommender system, search, experimentation, audience, and content AI solutions to drive user experience and growth.
The Daily
- Develop innovative data science solutions that utilize machine learning and deep learning algorithms, statistical and quantitative modelling approaches to support product, engineering, content, and marketing initiatives.
- Build and lead a world-class team of ML and AI scientists and engineers.
- Be a hands-on leader to mentor the team in latest machine learning and deep learning approaches, and to introduce new technologies and processes. Single headedly manage the MVP and PoCs
- Work with ML engineers to design solution architecture and develop scalable machine learning system to accelerate learning cycle.
- Identify data science opportunities that deliver business value.
- Develop ML/AI/CV roadmap and educate both internal and external stakeholders at all levels to drive implementation and measurement.
- Hands on experience in Image processing for auto industry
- BFSI domain knowledge is a plus
- Provide thought leadership to enable ML/AI applications.
- Manage products priorities and ensure timely delivery.
- Develop and evangelize best practices for scoping, building, validating, deploying, and monitoring ML/AI products.
- Prepare and present ML modelling results and analytical insights that help drive the business to senior leadership.
The Essentials
- 8 + years of work experience in Machine Learning, AI and Data Science with a proven track record to drive innovation and business impacts
- 4 + years of managing a team of data scientists, ML and AI researchers and engineers
- Strong machine learning, deep learning, and statistical modelling expertise, such as causal inference modelling, ensembles, neural networks, reinforcement learning, NLP, and computer vision
- Advanced knowledge of SQL and experience with big data platform (AWS, Snowflake, Spark, Google Cloud etc.)
- Proficiency in machine learning and deep learning languages and platforms (Python, R, TensorFlow, Keras, PyTorch, MXNet etc.)
- Experience in deploying machine learning algorithms and advanced modelling solutions
- Experience in developing advanced analytics and ML infrastructure and system
- Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment
- Strong communication skills and the ability to explain complex analysis and algorithms to non-technical audience
- Works effectively cross functional teams to build trusted partnership
- Working experience in digital media and entertainment industry preferred
- Experience with Agile methodologies preferred