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As a Lead Artificial Intelligence Engineer at Leapfrog Technology, you will be at the forefront of shaping the future of data-driven solutions. You'll lead a talented team, drive the development of innovative AI projects, and work collaboratively across functions to turn complex business challenges into actionable insights.
Key Responsibilities:
● Leadership Excellence: Lead and inspire a team of AI Engineers and Data Scientists, fostering a culture of innovation, collaboration, and continuous growth.
● End-to-End Ownership: Take full ownership of the AI project lifecycle, from ideation and design to development, deployment, and maintenance.
● Technological Innovation: Explore and assess emerging technologies to enhance the performance, maintainability, and reliability of AI systems.
● Engineering Best Practices: Apply robust software engineering practices to AI, including CI/CD pipelines, automation, and quality assurance.
● Architectural Leadership: Collaborate with technology experts to make informed architectural decisions, and ensure thorough technical documentation.
● Risk Mitigation: Proactively identify and address project risks, conduct root cause analysis, and implement preventive measures.
● Cross-functional Collaboration: Engage closely with cross-functional teams, including business stakeholders, product managers, software engineers, and data engineers, to deliver impactful data-driven solutions.
● Continuous Learning: Stay at the cutting edge of data science, ML, and AI developments, and leverage emerging technologies to solve complex business problems.
● Mentorship and Growth: Coach and motivate team members, identify training needs, and foster their professional development.
● Organizational Excellence: Actively uphold and promote the company's culture, processes, and standards to ensure consistent excellence in our work.
Job requirements
Education and Experience:
- A degree (Masters preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields.
- Minimum 6+ years of hands-on experience in AI/ML or Data Science, preferably in real industry settings, with a track record of building data products that have positively impacted customer satisfaction and revenue growth.
Technical Skills:
- Proficiency in a wide range of Machine Learning techniques and algorithms, with the ability to apply advanced analytics methods, including Bayesian statistics, clustering, text analysis, time series analysis, and neural networks on large-scale datasets.
- Expertise in at least one specialized area of application, such as Computer Vision or Natural Language Processing (NLP). (NLP Expertise preferred)
- Strong programming skills in Python, including expertise in the data ecosystem (Numpy, Scipy, Pandas, etc.) or equivalent skills in languages like R, Java, Scala, or Julia, with a focus on producing production-quality code.
- Hands-on experience with popular ML frameworks like Scikit-Learn, PyTorch, or TensorFlow.
- Expertise with Generative AI and Large Language Models (LLMs) along with their implementation in real-life applications.
- Experience building end-to-end ML systems (MLOps).
- Experience in deploying code in web frameworks such as Flask, FastAPI or Django.
- Experience working in a cloud environment like AWS, Azure, or GCP for ML work.
- Good grasp of SQL/NoSQL databases and scripting skills, particularly within analytics platforms and data warehouses.
- Good grasp of software engineering concepts (SDLC, Version Control, CI/CD, Containerization, Scalability and so on), programming concepts, and tools/platforms like Git and Docker.
- Bonus: Experience with Big Data technologies such as Apache Spark, Kafka, Kinesis, and cloud-based ML platforms like AWS SageMaker or GCP ML Engine.
- Bonus: Experience with data visualization and dashboard tools like Tableau or Power BI.
Soft Skills:
- Highly motivated, self-driven, entrepreneurial mindset, and capable of solving complex analytical problems under high-pressure situations.
- Ability to work with cross-functional and cross-regional teams.
- Ability to lead a team of Data/AI professionals and work with senior management, technological experts, and the product team.
- Excellent written and verbal communication skills, comfortable with client communication.
- Good leadership skills - ability to motivate and mentor team members, ability to plan and make sound decisions, ability to negotiate tactfully with the client and team.
- Results-oriented, customer-focused with a passion for resolving tough technical and operational challenges.
- Possess excellent analytical and problem-solving abilities.
- Good documentation skills.
- Experienced with Agile methodologies like Scrum/Kanban
JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.
Mon-Fri, In office role with excellent perks and benefits!
Key Responsibilities:
1. Design, develop, and maintain backend services and APIs using Node.js or Python, or Java.
2. Build and implement scalable and robust microservices and integrate API gateways.
3. Develop and optimize NoSQL database structures and queries (e.g., MongoDB, DynamoDB).
4. Implement real-time data pipelines using Kafka.
5. Collaborate with front-end developers to ensure seamless integration of backend services.
6. Write clean, reusable, and efficient code following best practices, including design patterns.
7. Troubleshoot, debug, and enhance existing systems for improved performance.
Mandatory Skills:
1. Proficiency in at least one backend technology: Node.js or Python, or Java.
2. Strong experience in:
i. Microservices architecture,
ii. API gateways,
iii. NoSQL databases (e.g., MongoDB, DynamoDB),
iv. Kafka
v. Data structures (e.g., arrays, linked lists, trees).
3. Frameworks:
i. If Java : Spring framework for backend development.
ii. If Python: FastAPI/Django frameworks for AI applications.
iii. If Node: Express.js for Node.js development.
Good to Have Skills:
1. Experience with Kubernetes for container orchestration.
2. Familiarity with in-memory databases like Redis or Memcached.
3. Frontend skills: Basic knowledge of HTML, CSS, JavaScript, or frameworks like React.js.
Who are we looking for?
We are looking for a Senior Data Scientist, who will design and develop data-driven solutions using state-of-the-art methods. You should be someone with strong and proven experience in working on data-driven solutions. If you feel you’re enthusiastic about transforming business requirements into insightful data-driven solutions, you are welcome to join our fast-growing team to unlock your best potential.
Job Summary
- Supporting company mission by understanding complex business problems through data-driven solutions.
- Designing and developing machine learning pipelines in Python and deploying them in AWS/GCP, ...
- Developing end-to-end ML production-ready solutions and visualizations.
- Analyse large sets of time-series industrial data from various sources, such as production systems, sensors, and databases to draw actionable insights and present them via custom dashboards.
- Communicating complex technical concepts and findings to non-technical stakeholders of the projects
- Implementing the prototypes using suitable statistical tools and artificial intelligence algorithms.
- Preparing high-quality research papers and participating in conferences to present and report experimental results and research findings.
- Carrying out research collaborating with internal and external teams and facilitating review of ML systems for innovative ideas to prototype new models.
Qualification and experience
- B.Tech/Masters/Ph.D. in computer science, electrical engineering, mathematics, data science, and related fields.
- 5+ years of professional experience in the field of machine learning, and data science.
- Experience with large-scale Time-series data-based production code development is a plus.
Skills and competencies
- Familiarity with Docker, and ML Libraries like PyTorch, sklearn, pandas, SQL, and Git is a must.
- Ability to work on multiple projects. Must have strong design and implementation skills.
- Ability to conduct research based on complex business problems.
- Strong presentation skills and the ability to collaborate in a multi-disciplinary team.
- Must have programming experience in Python.
- Excellent English communication skills, both written and verbal.
Benefits and Perks
- Culture of innovation, creativity, learning, and even failure, we believe in bringing out the best in you.
- Progressive leave policy for effective work-life balance.
- Get mentored by highly qualified internal resource groups and opportunity to avail industry-driven mentorship program, as we believe in empowering people.
- Multicultural peer groups and supportive workplace policies.
- Work from beaches, hills, mountains, and many more with the yearly workcation program; we believe in mixing elements of vacation and work.
Hiring Process
- Call with Talent Acquisition Team: After application screening, a first-level screening with the talent acquisition team to understand the candidate's goals and alignment with the job requirements.
- First Round: Technical round 1 to gauge your domain knowledge and functional expertise.
- Second Round: In-depth technical round and discussion about the departmental goals, your role, and expectations.
- Final HR Round: Culture fit round and compensation discussions.
- Offer: Congratulations you made it!
If this position sparked your interest, apply now to initiate the screening process.
Key skills : Python, Numpy, Panda, SQL, ETL
Roles and Responsibilities:
- The work will involve the development of workflows triggered by events from other systems
- Design, develop, test, and deliver software solutions in the FX Derivatives group
- Analyse requirements for the solutions they deliver, to ensure that they provide the right solution
- Develop easy to use documentation for the frameworks and tools developed for adaption by other teams
Familiarity with event-driven programming in Python
- Must have unit testing and debugging skills
- Good problem solving and analytical skills
- Python packages such as NumPy, Scikit learn
- Testing and debugging applications.
- Developing back-end components.
- Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
- Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
- Own the end-end process, from recognizing the problem to implementing the solution.
- Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
- Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.
Skills and Qualification
- 12 to 15 yrs of experience.
- An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
- Experience with text mining, parsing, and classification using state-of-the-art techniques.
- Experience with information retrieval, Natural Language Processing, Natural Language
- Understanding and Neural Language Modeling.
- Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
- Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
- Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
- Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.




