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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 you’ll 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. You’ll analyze new opportunities and ideas. You’ll 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),
- 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 – measured in hours and days, not weeks and months.
- Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
- Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ 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 don’t 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 don’t 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.
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.
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.
Work Location : Chennai
Experience Level : 5+yrs
Package : Upto 18 LPA
Notice Period : Immediate Joiners
It's a full-time opportunity with our client.
Mandatory Skills:Machine Learning,Python,Tableau & SQL
Job Requirements:
--2+ years of industry experience in predictive modeling, data science, and Analysis.
--Experience with ML models including but not limited to Regression, Random Forests, XGBoost.
--Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models.
--Experience writing code in Python and SQL with documentation for reproducibility.
--Strong Proficiency in Tableau.
--Experience handling big datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL.
--Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
--AWS Sagemaker experience is a plus not required.