Engineering Manager ML

ML Engineer

HackerPulse is a new and growing company. We help software engineers showcase their skills using AI powered profiles. As a Machine Learning Engineer, you will have the opportunity to contribute to the development and implementation of advanced Machine Learning (ML) and Natural Language Processing (NLP) solutions. You will play a crucial role in taking the innovative work done by our research team and turning it into practical solutions for production deployment. By applying to this job you agree to receive communication from us.

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Responsibilities:

1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.
2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.
3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.
4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.
5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.
6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.
7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.
8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.
9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.
10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.
11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.
12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.

Qualifications:

1. Degree in Computer Science or related discipline or equivalent practical experience, with a strong emphasis on machine learning and natural language processing.
2. Proven experience and in-depth knowledge of ML techniques, with a focus on implementing deep-learning approaches for NLP tasks in the context of productizing research goals.
3. Ability to apply engineering best practices to make architectural and design decisions aligned with functionalities, user experience, performance, reliability, and scalability in the development of deployable ML services.
4. Substantial experience in software development using Python, Java, and/or C or C++, with a particular emphasis on integrating machine learning models into production-ready software solutions.
5. Demonstrated problem-solving skills, showcasing the ability to address complex situations effectively, especially in the context of improving models, data engineering, and deployment processes.
6. Strong interpersonal and communication skills, essential for effective collaboration within cross-functional teams consisting of research, development, and frontend teams.
7. Proven time management skills to handle dynamic and agile development situations, ensuring timely delivery of solutions in a fast-paced environment.
8. Self-motivated contributor who frequently takes initiative to enhance the codebase and share best practices, contributing to the development of an open, transparent, and collaborative engineering culture.

About TensorIoT

• 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 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.

Job Description 

At TensorIoT India team, we look forward to bringing on board 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.

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. 

Minimum Requirements: 

• Masters + 6 years of work experience in Machine Learning Engineering OR B.Tech (Computer Science or related) + 8 years of work experience in Machine Learning Engineering 3 years of Cloud Experience.  
• Experience working with Generative AI (LLM), Prompt Engineering, Fine Tuning of LLMs.
• Hands-on experience in MLOps (model deployment, maintenance)
• Hands-on experience with Docker.
• Clear concepts of the following:
• - Supervised Learning, Unsupervised Learning, Reinforcement Learning
• - Statistical Modelling, Deep Learning
• - Interpretable Machine Learning  
• Well-rounded exposure to Computer Vision, Natural Language Processing, and Time-Series Analysis.
• Scientific & Analytical mindset, proactive learning, adaptability to changes. 
• Strong interpersonal and language skills in English, to communicate within the team and with the clients.

Preferred Qualifications: 

• PhD in the domain of Data Science / Machine Learning 
• M.Sc | M.Tech in the domain of Computer Science / Machine Learning 
• Some experience in creating cloud-native technologies, and microservices design. 
• Published scientific papers in the relevant domain of work. 

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.

Requirements

• Knowledge of multiple front-end languages and libraries (e.g. HTML/ CSS, Javascript (React.js), XML, jQuery)
• Knowledge of multiple back-end languages (e.g. C#, Java, Python) and JavaScript frameworks (e.g. Angular, React, Node.js)
• 8 - 10 years of overall experience including 3+ years in mentoring & leading a high-performance team
• Experience developing desktop and mobile applications
• Familiarity with databases (e.g. MySQL, MongoDB), web servers (e.g. Apache) and UI/UX design
• Knowledge of multiple front-end languages and libraries (e.g. HTML/ CSS, JavaScript, XML, jQuery)
• Have a strong understanding and appreciation for design first thinking and quality of user experience
• Be well-versed in sprint estimation, planning, tracking, change management and delivery, with prior experience of Agile-based development environments
• Strong command on vanilla/core JavaScript
• Knowledge of UI optimisations and performance.
• Deeper understanding of Chrome Dev Tools. Should understand the nuances of the timeline for perf monitoring.
• Deeper understanding of network layer, HTTP, HTTPS, cookies, local storage.
• Good communication skills, good visual design sense, in-depth experience in developing web-based applications.
• Strong technical aptitude and a good knowledge of CSS fundamentals

• SAAS
• Enterprise 
• fintech 
• Payments
• Healthcare

• See less

About Company

A fast-growing SaaS commerce company based in Bangalore with offices in Delhi, Mumbai, SF, Dubai, Singapore, and Dublin. We have three products in our portfolio: Plum, Empuls, and Compass. works with over 1000 global clients. We help our clients engage and motivate their employees, sales teams, channel partners, or consumers for better business results.

Engineering Manager 

Requirements:

Education - B.Tech/MCA or equivalent.

Overall 10 to 12 years of experience.

Agnostic/Polyglot with multiple tech stacks.

Worked on open source technologies – NodeJS, ReactJS, MySQL, NoSQL, MongoDB, Columnar DBs

Good experience with Front-end technologies like JavaScript frameworks, React, AngularJS.

Backend exposure – good knowledge of building API using Node or Lambda or python.

Good understanding of ELK, Kafka, Redis and CDN.

Worked on serverless technologies and good understanding of CMS.

Efficient in building microservices in combining server & front-end.

Good understanding of AWS and its technologies.

Should be innovative and communicative in approach and should be hands on coding guru

Will be responsible for the functional/technical track of a product.

Experience with Scaling SAAS products and ability to design from scratch.

Ability to manage a small team of 5 -10 Developers/QA Engineers and guide them on the design and coding best practices

Design and develop SaaS-based applications based on microservices architecture.

Work on the core backend and ensure it meets the performance benchmarks.

Work on the front-end with ReactJS.

Designing and developing APIs for the front-end to consume.

Constantly improve the architecture of the application by clearing the technical backlog.

Meeting both technical and consumer needs.

Staying abreast of developments in web applications and programming languages).

Responsibilities:

• Acting as an entrepreneur - taking ownership the problem statement end-to-end.

• Delivering direct value to the customer - and not just stop with internal delivery.

• Lead a diverse team of High performing Engineers - who set new standards everyday.

• Be a great engineer yourself - to be able to hire, mentor, and grow the engineering team.

• Estimate, plan, divide and conquer customer problem statements - through sturdily developed & performant technical solutions.

• Handle multiple competing priorities and ambiguity - all in a fast-paced, high growth environment.

Requirements:

• 7+ years of experience as an engineer or a lead - solving real world customer problems.

• 1-4 years of experience as a manager - having led high value delivering engineering teams.

• BE / B. Tech /M. Tech from a premier institute - preferably in Computer Science.

• Proven track record of building and managing high performing engineering teams.

• The ability to convince, negotiate and work with equally competent and smart stakeholders.

• Experience building complex technical solutions - highly scalable service-oriented architectures, distributed cloud-based systems - which power our FinTech products.

• Proven ability to present complex technical information in a clear and concise manner to executives and non-technical leaders.