Moative

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 an AI Engineer at Moative, you will be at the forefront of applying cutting-edge AI to solve real-world problems. You will be instrumental in designing and developing intelligent software solutions, leveraging the power of foundation models to automate and optimize critical workflows. Collaborating closely with domain experts, data scientists, and ML engineers, you will integrate advanced ML and AI technologies into both existing and new systems. This role offers a unique opportunity to explore innovative ideas, experiment with the latest foundation models, and build impactful products that directly enhance the lives of citizens by transforming how government services are delivered. You'll be working on challenging and impactful projects that move the needle on traditionally difficult-to-automate processes.

Responsibilities

• Utilize and adapt foundation models, particularly in vision and data extraction, as the core building blocks for developing impactful products aimed at improving government service delivery. This includes prompt engineering, fine-tuning, and evaluating model performance
• Architect, build, and deploy intelligent AI agent-driven workflows that automate and optimize key processes within government service delivery. This encompasses the full lifecycle from conceptualization and design to implementation and monitoring
• Contribute directly to enhancing our model evaluation and monitoring methodologies to ensure robust and reliable system performance. Proactively identify areas for improvement and implement solutions to optimize model accuracy and efficiency
• Continuously learn and adapt to the rapidly evolving landscape of AI and foundation models, exploring new techniques and technologies to enhance our capabilities and solutions

Who you are

You are a passionate and results-oriented engineer who is driven by the potential of AI/ML to revolutionize processes, enhance products, and ultimately improve user experiences. You thrive in dynamic environments and are comfortable navigating ambiguity. You possess a strong sense of ownership and are eager to take initiative, advocating for your technical decisions while remaining open to feedback and collaboration. 

You are adept at working with real-world, often imperfect data, and have a proven ability to develop, refine, and deploy AI/ML models into production in a cost-effective and scalable manner. You are excited by the prospect of directly impacting government services and making a positive difference in the lives of citizens

Skills & Requirements

• 3+ years of experience in programming languages such as Python or Scala
• Proficient knowledge of cloud platforms (e.g., AWS, Azure, GCP) and containerization, DevOps (Docker, Kubernetes)
• Tuning and deploying foundation models, particularly for vision tasks and data extraction
• Excellent analytical and problem-solving skills with the ability to break down complex challenges into actionable steps
• Strong written and verbal communication skills, with the ability to effectively articulate technical concepts to both technical and non-technical audiences

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 out 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. 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 work out of our offices in Chennai.

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.

Role

We seek experienced ML/AI professionals with strong backgrounds in computer science, software engineering, or related elds to join our Azure-focused MLOps team. If you’re passionate about deploying complex machine learning models in real-world settings, bridging the gap between research and production, and working on high-impact projects, this role is for you.

Work you’ll do

As an operations engineer, you’ll oversee the entire ML lifecycle on Azure—spanning initial proofs-of-concept to large-scale production deployments. You’ll build and maintain automated training, validation, and deployment pipelines using Azure DevOps, Azure ML, and related services, ensuring models are continuously monitored, optimized for performance, and cost-eective. By integrating MLOps practices such as MLow and CI/CD, you’ll drive rapid iteration and experimentation. In close collaboration with senior ML engineers, data scientists, and domain experts, you’ll deliver robust, production-grade ML solutions that directly impact business outcomes. 

Responsibilities

• ML-focused DevOps: Set up robust CI/CD pipelines with a strong emphasis on model versioning, automated testing, and advanced deployment strategies on Azure.
• Monitoring & Maintenance: Track and optimize the performance of deployed models through live metrics, alerts, and iterative improvements.
• Automation: Eliminate repetitive tasks around data preparation, model retraining, and inference by leveraging scripting and infrastructure as code (e.g., Terraform, ARM templates).
• Security & Reliability: Implement best practices for securing ML workows on Azure, including identity/access management, container security, and data encryption.
• Collaboration: Work closely with the data science teams to ensure model performance is within agreed SLAs, both for training and inference.

Skills & Requirements

• 2+ years of hands-on programming experience with Python (PySpark or Scala optional).
• Solid knowledge of Azure cloud services (Azure ML, Azure DevOps, ACI/AKS).
• Practical experience with DevOps concepts: CI/CD, containerization (Docker, Kubernetes), infrastructure as code (Terraform, ARM templates).
• Fundamental understanding of MLOps: MLow or similar frameworks for tracking and versioning.
• Familiarity with machine learning frameworks (TensorFlow, PyTorch, XGBoost) and how to operationalize them in production.
• Broad understanding of data structures and data engineering.

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, eiciency 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, x or improve – anything that isn’t done right, irrespective of who did it. Be selsh 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 work out of our offices in Chennai.

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. 

Role

We seek skilled and experienced data science/machine learning professionals with a strong background in at least one of mathematics, financial engineering, and electrical engineering, to join our Energy & Utilities team. If you are interested in artificial intelligence, excited about solving real business problems in the energy and utilities industry, and keen to contribute to impactful projects, this role is for you!

Work you’ll do

As a data scientist in the energy and utilities industry, you will perform quantitative analysis and build mathematical models to forecast energy demand, supply and strategies of efficient load balancing. You will work on models for short term and long term pricing, improving operational efficiency, reducing costs, and ensuring reliable power supply. You’ll work closely with cross-functional teams to deploy these models in solutions that provide insights/ solutions to real-world business problems. You will also be involved in conducting experiments, building POCs and prototypes.

Responsibilities

• Develop and implement quantitative models for load forecasting, energy production and distribution optimization.
• Analyze historical data to identify and predict extreme events, and measure impact of extreme events. Enhance existing pricing and risk management frameworks.
• Develop and implement quantitative models for energy pricing and risk management. Monitor market conditions and adjust models as needed to ensure accuracy and effectiveness.
• Collaborate with engineering and operations teams to provide quantitative support for energy projects. Enhance existing energy management systems and develop new strategies for energy conservation.
• Maintain and improve quantitative tools and software used in energy management.
• Support end-to-end ML/ AI model lifecycle - from data preparation, data analysis and feature engineering to model development, validation and deployment
• Collaborate with domain experts, engineers, and stakeholders in translating business problems into data-driven solutions
• Document methodologies and results, present findings and communicate insights to non-technical audiences

Skills & Requirements

• Strong background in mathematics, econometrics, electrical engineering, or a related eld.
• Experience data analysis, and quantitative modeling using programming languages such as Python or R.
• Excellent analytical and problem-solving skills.
• Strong understanding and experience with data analysis, statistical and mathematical concepts and ML algorithms
• Proficiency in Python and familiarity with basic Python libraries for data analysis and ML algorithms (such as NumPy, Pandas, ScikitLearn, NLTK).
• Strong communication skills
• Strong collaboration skills, ability to work with engineering and operations teams.
• A continuous learning attitude and a problem solving mind-set

Good to have -

• Knowledge of energy markets, regulations, and utility operation.
• Working knowledge of cloud platforms (e.g., AWS, Azure, GCP).
• Broad understanding of data structures and data engineering.

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, x 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 work out of our offices in Chennai.