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About Moative
Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.
Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.
Work youāll do
As a Junior ML/ AI Engineer, you will help design and develop intelligent software to solve business problems. You will collaborate with senior ML engineers, data scientists and domain experts to incorporate ML and AI technologies into existing or new workflows. Youāll analyze new opportunities and ideas. Youāll train and evaluate ML models, conduct experiments, help develop PoCs and prototypes.
Responsibilities
- Designing, training, improving & launching machine learning models using tools such as XGBoost, Tensorflow, PyTorch.
- Contribute directly to the improvement of the way we evaluate and monitor model and system performances.
- Proposing and implementing ideas that directly impact our operational and strategic metrics.
Who you are
You are an engineer who is passionate about using AL/ML to improve processes, products and delight customers. You have experience working with less than clean data, developing and tweaking ML models, and are interested deeply in getting these models into production as cost effectively as possible. You thrive on taking initiatives, are very comfortable with ambiguity and can passionately defend your decisions.
Requirements and skills
- 3+ years of experience in programming languages such as Python, PySpark, or Scala.
- Proficient knowledge of cloud platforms (e.g., AWS, Azure, GCP) and containerization, DevOps (Docker, Kubernetes),Ā
- Beginner level knowledge of MLOps practices and platforms like MLflow.
- Strong understanding of ML algorithms and frameworks (e.g., TensorFlow, PyTorch).
- Broad understanding of data structures, data engineering, statistical methodologies and machine learning models.
Working at Moative
Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less. Here are some of our guiding principles:
- Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast ā measured in hours and days, not weeks and months.
- Own the canvas. Throw yourself in to build, fix or improve ā anything that isnāt done right, irrespective of who did it. Be selfish about improving across the organization ā because once the rot sets in, we waste years in surgery and recovery.
- Use data or donāt use data. Use data where you ought to but not as a ācover-my-backā political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
- Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you donāt need a person with the highest title to say that loud.
- High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We donāt like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.
If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.Ā Ā
That said, you should demonstrate that you are in the 90th percentile or above. This may mean that you have studied in top-notch institutions, won competitions that are intellectually demanding, built something of your own, or rated as an outstanding performer by your current or previous employers.Ā
The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to be present in the city. We intend to move to a hybrid model in a few months time.
Role Overview:
We are seeking a highly skilled and motivated Data Scientist to join our growing team. The ideal candidate will be responsible for developing and deploying machine learning models from scratch to production level, focusing on building robust data-driven products. You will work closely with software engineers, product managers, and other stakeholders to ensure our AI-driven solutions meet the needs of our users and align with the company's strategic goals.
Key Responsibilities:
- Develop, implement, and optimize machine learning models and algorithms to support product development.
- Work on the end-to-end lifecycle of data science projects, including data collection, preprocessing, model training, evaluation, and deployment.
- Collaborate with cross-functional teams to define data requirements and product taxonomy.
- Design and build scalable data pipelines and systems to support real-time data processing and analysis.
- Ensure the accuracy and quality of data used for modeling and analytics.
- Monitor and evaluate the performance of deployed models, making necessary adjustments to maintain optimal results.
- Implement best practices for data governance, privacy, and security.
- Document processes, methodologies, and technical solutions to maintain transparency and reproducibility.
Qualifications:
- Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field.
- 5+ years of experience in data science, machine learning, or a related field, with a track record of developing and deploying products from scratch to production.
- Strong programming skills in Python and experience with data analysis and machine learning libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch).
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker).
- Proficiency in building and optimizing data pipelines, ETL processes, and data storage solutions.
- Hands-on experience with data visualization tools and techniques.
- Strong understanding of statistics, data analysis, and machine learning concepts.
- Excellent problem-solving skills and attention to detail.
- Ability to work collaboratively in a fast-paced, dynamic environment.
Preferred Qualifications:
- Knowledge of microservices architecture and RESTful APIs.
- Familiarity with Agile development methodologies.
- Experience in building taxonomy for data products.
- Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
Roles & Responsibilities:
-Adopt novel and breakthrough Deep Learning/Machine Learning technology to fully solve real world problems for different industries. -Develop prototypes of machine learning models based on existing research papers.
-Utilize published/existing models to meet business requirements. Tweak existing implementations to improve efficiencies and adapt for use-case variations.
-Optimize machine learning model training and inference time. -Work closely with development and QA teams in transitioning prototypes to commercial products
-Independently work end-to-end from data collection, preparation/annotation to validation of outcomes.
-Define and develop ML infrastructure to improve efficiency of ML development workflows.
Must Have:
- Experience in productizing and deployment of ML solutions.
- AI/ML expertise areas: Computer Vision with Deep Learning. Experience with object detection, classification, recognition; document layout and understanding tasks, OCR/ICR
. - Thorough understanding of full ML pipeline, starting from data collection to model building to inference.
- Experience with Python, OpenCV and at least a few framework/libraries (TensorFlow / Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)
- Years with relevant experience:
5+ -Experience or Knowledge in ML OPS.
Good to Have: NLP: Text classification, entity extraction, content summarization. AWS, Docker.
Do you want to help build real technology for a meaningful purpose? Do you want to contribute to making the world more sustainable, advanced and accomplished extraordinary precision in Analytics?Ā
What is your role?
As a Computer Vision & Machine Learning Engineer at Datasee.AI, youāll be core to the development of our robotic harvesting systemās visual intelligence. Youāll bring deep computer vision, machine learning, and software expertise while also thriving in a fast-paced, flexible, and energized startup environment. As an early team member, youāll directly build our success, growth, and culture. Youāll hold a significant role and are excited to grow your role as Datasee.AI grows.Ā
What youāll do
- You will be working with the core R&D team which drives the computer vision and image processing development.Ā
- Build deep learning model for our data and object detection on large scale images.Ā
- Design and implement real-time algorithms for object detection, classification, tracking, and segmentationĀ
- Coordinate and communicate within computer vision, software, and hardware teams to design and execute commercial engineering solutions.Ā
- Automate the workflow process between the fast-paced data delivery systems.Ā
What we are looking for
- 1 to 3+ years of professional experience in computer vision and machine learning.
- Extensive use of PythonĀ
- Experience in python libraries such as OpenCV, Tensorflow and NumpyĀ
- Familiarity with a deep learning library such as Keras and PyTorchĀ
- Worked on different CNN architectures such as FCN, R-CNN, Fast R-CNN and YOLO
- Experienced in hyperparameter tuning, data augmentation, data wrangling, model optimization and model deployment
- B.E./M.E/M.Sc. Computer Science/Engineering or relevant degree
- Dockerization, AWS modules and Production level modelling
- Basic knowledge of the Fundamentals of GIS would be added advantage
Prefered Requirements
- Experience with Qt, Desktop application development, Desktop AutomationĀ
- Knowledge on Satellite image processing, Geo-Information System, GDAL, Qgis and ArcGIS
About Datasee.AI:
Datasee>AI, Inc. is an AI driven Image Analytics company offering Asset Management solutions for industries in the sectors of Renewable Energy, Infrastructure, Utilities & Agriculture. With core expertise in Image processing, Computer Vision & Machine Learning, Takvaviyaās solution provides value across the enterprise for all the stakeholders through a data driven approach.Ā
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With Sales & Operations based out of US, Europe & India, Datasee.AI is a team of 32 people located across different geographies and with varied domain expertise and interests.Ā
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A focused and happy bunch of people who take tasks head-on and build scalable platforms and products.
- 3+ years experience in practical implementation and deployment of ML based systems preferred.
- BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
- Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
- Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
- Experience in working on modeling graph structures related to spatiotemporal systems
- Programming skills in Python
- Experience in developing and deploying on cloud (AWS or Google or Azure)
- Good verbal and written communication skills
- Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow