Data Science Engineer-MNC Company-Chennai
Position: Manager/Head- Data Scientist/Machine Learning Engineer
- Algorithm Development: Develop cutting-edge algorithms and predictive models to enhance customer experience, optimize inventory management, and drive sales growth
- AI/ML Model Building: Utilize expertise in data science and machine learning to create scalable AI models specifically tailored for both online platforms and brick-and-mortar stores, aiming to improve operational efficiency and customer engagement.
- Ecommerce Optimization: Collaborate with cross-functional teams to implement data-driven solutions for personalized recommendations, demand forecasting, and dynamic pricing strategies to drive online sales and enhance customer satisfaction.
- Deep Learning & Image Recognition: Leverage advanced techniques in deep learning and image recognition to develop innovative solutions for product categorization, visual search, and inventory tracking, optimizing product discovery and inventory management.
- Python Development: Proficiency in Python programming is essential for designing, implementing, and maintaining robust and scalable machine learning pipelines and models, ensuring efficient deployment and integration into existing systems.
Qualifications and Experience:
- Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, or related fields.
- 3 to 4 years of hands-on experience in data science, machine learning, and deep learning, preferably within the ecommerce or retail sector.
- Proven track record of successful implementation of AI/ML models with tangible business impact.
- Strong proficiency in Python, along with familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience working with image data, including feature extraction, object detection, and classification.
- Excellent problem-solving skills, ability to work independently, and communicate complex technical concepts effectively to diverse stakeholders.
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About UpSolve
We built and deliver complex AI solutions which help drive business decisions faster and more accurately. We are a typical AI company and have a range of solutions developed on Video, Image and Text.
What you will do
- Stay informed on new technologies and implement cautiously
- Maintain necessary documentation for the project
- Fix the issues reported by application users
- Plan, build, and design solutions with a mental note of future requirements
- Coordinate with the development team to manage fixes, code changes, and merging
Location: Mumbai
Working Mode: Remote
What are we looking for
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
- Minimum 2 years of professional experience in software development, with a focus on machine learning and full stack development.
- Strong proficiency in Python programming language and its machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
- Experience in developing and deploying machine learning models in production environments.
- Proficiency in web development technologies including HTML, CSS, JavaScript, and front-end frameworks such as React, Angular, or Vue.js.
- Experience in designing and developing RESTful APIs and backend services using frameworks like Flask or Django.
- Knowledge of databases and SQL for data storage and retrieval.
- Familiarity with version control systems such as Git.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work effectively in a fast-paced and dynamic team environment.
- Good to have Cloud Exposure
Responsibilities:
- Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
- Design and implement cloud solutions, build MLOps on the cloud (preferably AWS)
- Work with workflow orchestration tools like Kubeflow, Airflow, Argo, or similar tools
- Data science models testing, validation, and test automation.
- Communicate with a team of data scientists, data engineers, and architects, and document the processes.
Eligibility:
- Rich hands-on experience in writing object-oriented code using python
- Min 3 years of MLOps experience (Including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning, and Automated pipelines)
- Understanding of Data Structures, Data Systems, and software architecture
- Experience in using MLOps frameworks like Kubeflow, MLFlow, and Airflow Pipelines for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc. )
Principal Accountabilities :
1. Good in communication and converting business requirements to functional requirements
2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data
3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.
5. Experience in SOTA Deep Learning techniques to solve NLP problems.
6. End-to-end data collection, model development and testing, and integration into production environments.
7. Build and prototype analysis pipelines iteratively to provide insights at scale.
8. Experience in querying different data sources
9. Partner with developers and business teams for the business-oriented decisions
10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
analyses
● Should be comfortable in going through open-source code and reading research papers.
Responsibilities:
- Improve robustness of Leena AI current NLP stack
- Increase zero shot learning capability of Leena AI current NLP stack
- Opportunity to add/build new NLP architectures based on requirements
- Manage End to End lifecycle of the data in the system till it achieves more than 90% accuracy
- Manage a NLP team
Page BreakRequirements:
- Strong understanding of linear algebra, optimisation, probability, statistics
- Experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation
- Experience in deploying NLP architectures in production
- Understanding of latest NLP architectures like transformers is good to have
- Experience in adversarial attacks/robustness of DNN is good to have
- Experience with Python Web Framework (Django), Analytics and Machine Learning frameworks like Tensorflow/Keras/Pytorch.
About Quidich
http://www.quidich.com">Quidich Innovation Labs pioneers products and customized technology solutions for the Sports Broadcast & Film industry. With a mission to bring machines and machine learning to sports, we use camera technology to develop services using remote controlled systems like drones and buggies that add value to any broadcast or production. Quidich provides services to some of the biggest sports & broadcast clients in India and across the globe. A few recent projects include Indian Premier League, ICC World Cup for Men and Women, Kaun Banega Crorepati, Bigg Boss, Gully Boy & Sanju.
What’s Unique About Quidich?
- Your work will be consumed by millions of people within months of your joining and will impact consumption patterns of how live sport is viewed across the globe.
- You work with passionate, talented, and diverse people who inspire and support you to achieve your goals.
- You work in a culture of trust, care, and compassion.
- You have the autonomy to shape your role, and drive your own learning and growth.
Opportunity
- You will be a part of world class sporting events
- Your contribution to the software will help shape the final output seen on television
- You will have an opportunity to work in live broadcast scenarios
- You will work in a close knit team that is driven by innovation
Role
We are looking for a tech enthusiast who can work with us to help further the development of our Augmented Reality product, https://www.quidich.com/services/spatio">Spatio, to keep us ahead of the technology curve. We are one of the few companies in the world currently offering this product for live broadcast. We have a tight product roadmap that needs enthusiastic people to solve problems in the realm of software development and computer vision systems. Qualified candidates will be driven self-starters, robust thinkers, strong collaborators, and adept at operating in a highly dynamic environment. We look for candidates that are passionate about the product and embody our values.
Responsibilities
- Working with the research team to develop, evaluate and optimize various state of the art algorithms.
- Deploying high performance, readable, and reliable code on edge devices or any other target environments.
- Continuously exploring new frameworks and identifying ways to incorporate those in the product.
- Collaborating with the core team to bring ideas to life and keep pace with the latest research in Computer Vision, Deep Learning etc.
Minimum Qualifications, Skills and Competencies
- B.E/B.Tech or Masters in Computer Science, Mathematics or relevant experience
- 3+ years of experience in computer vision algorithms like - sfm/SLAM, optical flow, visual-inertial odometry
- Experience in sensor fusion (camera, imu, lidars) and in probabilistic filters - EKF, UKF
- Proficiency in programming - C++ and algorithms
- Strong mathematical understanding - linear algebra, 3d-geometry, probability.
Preferred Qualifications, Skills and Competencies
- Proven experience in optical flow, multi-camera geometry, 3D reconstruction
- Strong background in Machine Learning and Deep Learning frameworks.
Reporting To: Product Lead
Joining Date: Immediate (Mumbai)
About the Company
- 💰 Early-stage, ed-tech, funded, growing, growing fast.
- 🎯 Mission Driven: Make Indonesia competitive on a global scale.
- 🥅 Build the best educational content and technology to advance STEM education
- 🥇 Students-First approach
About the People
- ❤️ Love what we do
- 🎮 Committed to making learning fun, accessible, and safe
- 🤝 Teams are better. We value ownership, responsibility, transparency
- 🌏 Global, diverse backgrounds. Been there, done that.
What does it look like one year from now?
- CoLearn has grown so much, and you’ve been an important part of the growth. You solved hard problems that many didn’t know existed.
- You’ve led the data science function and laid out the roadmap, implemented best practices, and grown the team. You’ve executed mission-critical projects. Congratulations!
- You’re exploring what Data Science can do for the students, parents, teachers, educators.
- You’ve been speaking at Data Science conferences about the image recognition system we built from scratch. You casually threw in the semantic search engine on slide 77.
- The engineering and product teams are your friends. The teams take cross-functional collaboration, testing, and modeling for granted. It’s their second nature.
- You have an encyclopedic knowledge of CoLearn’s data structures and metrics, and you’ve often provided key ideas for the product.
About you
- Highly-skilled and experienced Data Scientist and leader
- You are interested in creating next-gen data-powered education tech products.
- You’ve worked in a Data Science role before where you took a data product to market
- You are comfortable working with unknowns, evaluating the data, and applying scientific techniques to business problems and products
- You’ve built platforms and systems from scratch
- You have a track record of developing and deploying data-science models to production
Let’s talk tech
- End-to-end AI/ML systems in the cloud, including data processing, feature engineering, and tuning of ML models in training and production (MLOps) — with both structured and unstructured data.
- Deep Learning and Computer Vision models, ideally in a production environment
- Hands-on Python/SQL, scikit-learn, Keras, PyTorch, Tensorflow, MXnet, etc.
- Experience in Scala/Java/Go/C/C++ is a plus plus
- Airflow/Luigi/Oozie and the likes
- Familiarity with cloud deployment strategies (AWS/GCP) to deploy at scale
Track record
- B.S./B.E./M.S./PhD in a quantitative field such as Computer Science, Engineering, Math, Statistics or equivalent years of experience
- 10+ years of experience in data science, algorithmic engineering, and machine learning. Preferably solved problems from scratch to scale
- Experience in hiring, managing highly-performant teams, and mentoring data science, data engineering, and analytics teams
- Experience developing a data science strategy, building the roadmap, and leading the execution
- Track record of recruiting talent in analytics and data science
You will make us go 😍 if:
- You’ve won algorithm and machine learning competitions such as ACM and Kaggle
- You have research publications and citations in top tier journals
- You have a portfolio of side projects and can show it to us
Advanced degree in computer science, math, statistics or a related discipline ( Must have master degree )
Extensive data modeling and data architecture skills
Programming experience in Python, R
Background in machine learning frameworks such as TensorFlow or Keras
Knowledge of Hadoop or another distributed computing systems
Experience working in an Agile environment
Advanced math skills (Linear algebra
Discrete math
Differential equations (ODEs and numerical)
Theory of statistics 1
Numerical analysis 1 (numerical linear algebra) and 2 (quadrature)
Abstract algebra
Number theory
Real analysis
Complex analysis
Intermediate analysis (point set topology)) ( important )
Strong written and verbal communications
Hands on experience on NLP and NLG
Experience in advanced statistical techniques and concepts. ( GLM/regression, Random forest, boosting, trees, text mining ) and experience with application.
About Turing:
Turing enables U.S. companies to hire the world’s best remote software engineers. 100+ companies including those backed by Sequoia, Andreessen, Google Ventures, Benchmark, Founders Fund, Kleiner, Lightspeed, and Bessemer have hired Turing engineers. For more than 180,000 engineers across 140 countries, we are the preferred platform for finding remote U.S. software engineering roles. We offer a wide range of full-time remote opportunities for full-stack, backend, frontend, DevOps, mobile, and AI/ML engineers.
We are growing fast (our revenue 15x’d in the past 12 months and is accelerating), and we have raised $14M in seed funding (https://tcrn.ch/3lNKbM9">one of the largest in Silicon Valley) from:
- Facebook’s 1st CTO and Quora’s Co-Founder (Adam D’Angelo)
- Executives from Google, Facebook, Square, Amazon, and Twitter
- Foundation Capital (investors in Uber, Netflix, Chegg, Lending Club, etc.)
- Cyan Banister
- Founder of Upwork (Beerud Sheth)
We also raised a much larger round of funding in October 2020 that we will be publicly announcing over the coming month.
Some articles about Turing:
- https://techcrunch.com/2020/08/25/turing-raises-14m-to-help-source-vet-place-and-manage-remote-developers-in-tech-jobs/">TechCrunch: Turing raises $14M seed to help source, vet, place, and manage remote developers
- https://www.theinformation.com/articles/six-startups-prospering-during-coronavirus">The Information: Six Startups Prospering During Coronavirus
- https://medium.com/@cyanbanister/turing-helps-the-world-level-up-ff44b4e6415d">Cyan Banister: Turing Helps the World Level Up
- https://turing.com/boundarylessblog/2019/10/the-future-of-work-is-remote/the-future-of-work/">Jonathan Siddharth (Turing CEO): The Future of Work is Remote.
Turing is led by successful repeat founders Jonathan Siddharth and Vijay Krishnan, whose last A.I. company leveraged elite remote talent and had a successful acquisition. (https://techcrunch.com/2017/02/23/revcontent-acquires-rover/">Techcrunch story). Turing’s leadership team is composed of ex-Engineering and Sales leadership from Facebook, Google, Uber, and Capgemini.
About the role:
Software developers from all over the world have taken 200,000+ tests and interviews on Turing. Turing has also recommended thousands of developers to its customers and got customer feedback in terms of customer interview pass/fail data and data from the success of the collaboration with a U.S customer. This generates a massive proprietary dataset with a rich feature set comprising resume and test/interview features and labels in the form of actual customer feedback. Continuing rapid growth in our business creates an ever-increasing data advantage for us.
We are looking for a Machine Learning Scientist who can help solve a whole range of exciting and valuable machine learning problems at Turing. Turing collects a lot of valuable heterogeneous signals about software developers including their resume, GitHub profile and associated code and a lot of fine-grained signals from Turing’s own screening tests and interviews (that span various areas including Computer Science fundamentals, project ownership and collaboration, communication skills, proactivity and tech stack skills), their history of successful collaboration with different companies on Turing, etc.
A machine learning scientist at Turing will help create deep developer profiles that are a good representation of a developer’s strengths and weaknesses as it relates to their probability of getting successfully matched to one of Turing’s partner companies and having a fruitful long-term collaboration. The ML scientist will build models that are able to rank developers for different jobs based on their probability of success at the job.
You will also help make Turing’s tests more efficient by assessing their ability to predict the probability of a successful match of a developer with at least one company. The prior probability of a registered developer getting matched with a customer is about 1%. We want our tests to adaptively reduce perplexity as steeply as possible and move this probability estimate rapidly toward either 0% or 100%; maximize expected information-gain per unit time in other words.
As an ML Scientist on the team, you will have a unique opportunity to make an impact by advancing ML models and systems, as well as uncovering new opportunities to apply machine learning concepts to Turing product(s).
This role will directly report to Turing’s founder and CTO, https://www.linkedin.com/in/vijay0/">Vijay Krishnan. This is his https://scholar.google.com/citations?user=uCRc7DgAAAAJ&hl=en">Google Scholar profile.
Responsibilities:
- Enhance our existing machine learning systems using your core coding skills and ML knowledge.
- Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems.
- Utilize state-of-the-art ML modeling techniques to predict user interactions and the direct impact on the company’s top-line metrics.
- Design features and builds large scale recommendation systems to improve targeting and engagement.
- Identify new opportunities to apply machine learning to different parts of our product(s) to drive value for our customers.
Minimum Requirements:
- BS, MS, or Ph.D. in Computer Science or a relevant technical field (AI/ML preferred).
- Extensive experience building scalable machine learning systems and data-driven products working with cross-functional teams
- Expertise in machine learning fundamentals, applicable to search - Learning to Rank, Deep Learning, Tree-Based Models, Recommendation Systems, Relevance and Data mining, understanding of NLP approaches like W2V or Bert.
- 2+ years of experience applying machine learning methods in settings like recommender systems, search, user modeling, graph representation learning, natural language processing.
- Strong understanding of neural network/deep learning, feature engineering, feature selection, optimization algorithms. Proven ability to dig deep into practical problems and choose the right ML method to solve them.
- Strong programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools.
- Good understanding of mathematical foundations of machine learning algorithms.
- Ability to be available for meetings and communication during Turing's "coordination hours" (Mon - Fri: 8 am to 12 pm PST).
Other Nice-to-have Requirements:
- First author publications in ICML, ICLR, NeurIPS, KDD, SIGIR, and related conferences/journals.
- Strong performance in Kaggle competitions.
- 5+ years of industry experience or a Ph.D. with 3+ years of industry experience in applied machine learning in similar problems e.g. ranking, recommendation, ads, etc.
- Strong communication skills.
- Experienced in leading large-scale multi-engineering projects.
- Flexible, and a positive team player with outstanding interpersonal skills.