Mid Level Machine Learning Engineer / Data Scientist
Machine Learning (ML)
Data ScienceTensorIoT:
- AWS Advanced Consulting Partner (for ML and GenAI solutions)
- Pioneers in IoT and Generative AI products.
- Committed to diversity and inclusion in our teams.
TensorIoT is an AWS Advanced Consulting Partner. We assist companies to realize the value and efficiency of the AWS ecosystem. From building Proof of Concepts and Product Prototypes to production-ready applications, we analyze complex business problems every day and develop solutions to drive customers’ success.
The founders of TensorIoT, have previously helped build world-class IoT and AI platforms in AWS and Google. Our mission now is to help connect devices and make them intelligent. We firmly believe in the transformative power of smart devices to enhance our quality of life.
TensorIoT is proud to be an equal opportunity employer. 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.
Job Description
At the TensorIoT India team, we look forward to bringing on board mid-level and senior Machine Learning Engineers / Data Scientists. In this section, we briefly describe the work role, the minimum and the preferred requirements to qualify for the first round of the selection process. Please note: A candidate needs to qualify at least 4 of the 7 preferred qualifications listed below, to be eligible for the task / first round of interviews.
What are the kinds of tasks Data Scientists do at TensorIoT?
As a Data Scientist, the kinds of tasks revolve around the data that we have and the business objectives of the client. The tasks generally involve: Studying, understanding, and analyzing datasets; feature engineering, proposing and solutions, evaluating the solution scientifically, and communicating with the client. Implementing ETL pipelines with database/data lake tools. Conduct and present scientific research/experiments within the team and to the client.
Preferred Requirements:
- PhD in the domain of Data Science / Machine Learning
- M.Sc | M.Tech in the domain of Computer Science / Machine Learning
- Hands-on experience in MLOps (model deployment, maintenance).
- Some experience working with Generative AI (LLM).
- Some experience in creating cloud-native technologies, and microservices design.
- Well-rounded exposure to Computer Vision, Natural Language Processing, and Time-Series Analysis.
- Hands-on experience with Docker.
Minimum Requirements:
- Masters + 3 years of work experience in Machine Learning Engineering OR B.Tech (Computer Science or related) + 5 years of work experience in Machine Learning Engineering 1 year of Cloud Experience.
- Clear concepts of the following:
- - Supervised Learning, Unsupervised Learning, Reinforcement Learning
- - Statistical Modelling, Deep Learning
- - Interpretable Machine Learning
- - Linear Algebra
- Scientific & Analytical mindset, proactive learning, adaptability to changes.
- Strong interpersonal and language skills in English, to communicate within the team and with the clients.
CV Tips:
Your CV is an integral part of your application process. We would appreciate it if the CV prioritizes the following:
- Focus:
- More focus on technical skills relevant to the job description.
- Less or no focus on your roles and responsibilities as a manager, team lead, etc.
- Less or no focus on the design aspect of the document.
- Regarding the projects you completed in your previous companies,
- Mention the problem statement very briefly.
- Your role and responsibilities in that project.
- Technologies & tools used in the project.
- Always good to mention (if relevant):
- Scientific papers published, Master Thesis, Bachelor Thesis.
- Github link, relevant blog articles.
- Link to LinkedIn profile.
- Mention skills that are relevant to the job description and you could demonstrate during the interview/tasks in the selection process.
We appreciate your interest in the company and look forward to your application.
Shubham Vishwakarma
Full Stack Developer - Averlon
About TensorIoT Software Services Private Limited, India
About
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.
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Amazon Web Services (AWS)Machine Learning (ML)Company video
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Simply put, we connect devices and make them smarter. We’ve helped over 150 clients expand the possible through intelligent innovation, and we're just getting started.
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DockerAmazon Web Services (AWS)|
Job Title: |
Senior Cloud Infrastructure Engineer (AWS) |
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Department & Team |
Technology |
Location: |
India /UK / Ukraine |
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Reporting To: |
Infrastructure Services Manager |
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Role Purpose: |
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The purpose of the role is to ensure high systems availability across a multi-cloud environment, enabling the business to continue meeting its objectives.
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Responsibilities: |
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Operations · Deliver end to end technical and user support across all platforms (On-premise, Azure, AWS) · Day to day, fully hands-on OS management responsibilities (Windows and Linux operating systems) · Ensure robust server patching schedules are in place and meticulously followed to help reduce security related incidents. · Contribute to continuous improvement efforts around cost optimisation, security enhancement, performance optimisation, operational efficiency and innovation. · Take an ownership role in delivering technical projects, ensuring best practise methods are followed. · Design and deliver solutions around the concept of “Planning for Failure”. Ensure all solutions are deployed to withstand system / AZ failure. · Work closely with Cloud Architects / Infrastructure Services Manager to identify and eliminate “waste” across cloud platforms. · Assist several internal DevOps teams with day to day running of pipeline management and drive standardisation where possible. · Ensure all Client data in all forms are backed up in a cost-efficient way. · Use the appropriate monitoring tools to ensure all cloud / on-premise services are continuously monitored. · Drive utilisation of most efficient methods of resource deployment (Terraform, CloudFormation, Bootstrap) · Drive the adoption, across the business, of serverless / open source / cloud native technologies where applicable. · Ensure system documentation remains up to date and designed according to AWS/Azure best practise templates. · Participate in detailed architectural discussions, calling on internal/external subject matter experts as needed, to ensure solutions are designed for successful deployment. · Take part in regular discussions with business executives to translate their needs into technical and operational plans. · Engaging with vendors regularly in terms of verifying solutions and troubleshooting issues. · Designing and delivering technology workshops to other departments in the business. · Takes initiatives for improvement of service delivery. · Ensure that Client delivers a service that resonates with customer’s expectations, which sets Client apart from its competitors. · Help design necessary infrastructure and processes to support the recovery of critical technology and systems in line with contingency plans for the business. · Continually assess working practices and review these with a view to improving quality and reducing costs. · Champions the new technology case and ensure new technologies are investigated and proposals put forward regarding suitability and benefit. · Motivate and inspire the rest of the infrastructure team and undertake necessary steps to raise competence and capability as required. · Help develop a culture of ownership and quality throughout the Infrastructure Services team.
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Skills & Experience: |
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Behavioural Fit: |
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Role Key Performance Indicators: |
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon