AI/ML Application Developer

3 weeks ago

Mumbai, India Antal TECH jobs Full time

About the role:

We are seeking highly skilled and motivated AI/GenAI Full Stack Optimization & Software Developer to join our innovative AI/GenAI Center of Excellence Data & Analytics, Data Science team at our client office in Mumbai. This role will have end-to-end visibility on our Data Science practice and understand all aspect of an AI/GenAI/ML solution: from business requirements, infrastructure, implementation & operations. This role is expected to work with project teams directly and coordinate with other MDS and Data Science groups to successfully deliver Data Science use-cases. In this role, you will play a pivotal role in planning, developing, and optimizing the UI/back-end of our AI/GenAI products. This position offers a unique opportunity to collaborate with cross-functional teams, drive business value, and shape the future of our AI/GenAI Center of Excellence practices.


Responsibilities: Must have skills

1. Front-end & back-end development:

  • Being a part of a team of Full Stack development team, that bring functional & Technical excellence together to ensure Data Science use-cases are set-up right with right technology and delivered in the most efficient manner, in term of performance, cost & accuracy.
  • Ensures the establishment of AI/ML/GenAI Apps user interface and its back end are accommodated with the with optimal performance, efficiency, and cost-effectiveness to is to ensure that the application is accessible, visually appealing, and easy to use for end users.
  • Translates design mockups into functional web or mobile applications using HTML, CSS, and JavaScript.
  • Govern backend cloud ML/AI Apps architecture and provide support to the Mondelez Data Science/AI/MLOps team.
  • Implement gateways as rate limiters to control request rates per second, preventing system overload.
  • Create robust APIs that allow the front-end to interact seamlessly with the server-side logic and AI functionalities.
  • Developing the logic that handles user requests, processes them, and returns the necessary responses. This often involves talking to different AI models and handling complex logic.
  • Conduct research, evaluation, and optimization of software architecture components for cloud-based platforms.
  • Optimize existing solutions and facilitate the onboarding of new solutions.
  • Support AI production applications and ensure compliance with Enterprise Architecture guidelines & processes.
  • Own onboarding protocols and documentation of the implemented full tech stack.
  • Collaborate with the D4GV Platform team for activation and optimization.
  • Lead and consult AI/GenAI Apps product onboarding and plan/optimize platform capacity.
  • Provide guidelines and schemas for required full-stack software.
  • Validate Platform changes through User Acceptance Testing (UAT).
  • Stay informed about new capabilities and plan for their enablement (platform innovation).
  • Conduct initial assessments for AI/GenAI Apps Self-Service requests in synergy with DS/MLOps teams.
  • Identify key metrics for business use cases and showcase the value of AI solutions.
  • Act as a consultant for the implementation of DS/AI Web Apps products.
  • Collaborate with Platform, Cloud, Architecture, Data Science, MLOps, CoP, and Business teams.


Nice to have skills:-

1. Architecture Set-Up and Review:

  • Provide end to end DS solution architecture guidance: What technical architecture for what type of model and solution.
  • Technical Architecture leadership: recommend what cluster, tool, solution, is best to fulfil a business problem (Databricks, Vertex AI, Azure AI, GCP, React, Python/R/Scala, etc.)
  • Ensure compliance with Enterprise Architecture Guidelines & process.
  • Owns the onboarding protocols, documents.


Requirements:

  • Bachelors degree in Computer Science, Software Engineering, MLOps Engineering, or related field and at least 4 years of industry experience. Advanced degree (Master's or Ph.D.) is preferred.
  • Over 10 years of professional experience in Software Architecture, Full Stack Development , and Machine Learning/MLOps . Experience with building Apps.
  • Has strong proficiency in DataBricks and experience with other programming languages like Python, PySpark, SQL , etc.
  • Experience working with modern web services architectures and cloud platforms, particularly Azure, GCP, and AWS clouds.
  • Has knowledge of data engineering using frameworks such as Spark, distributed SQL, and NoSQL query engines.
  • Has experience in setting up the analytical data set using ETL tools or Programming languages for advanced analytics models.
  • Proven experience as a Full-Stack Developer, with expertise in both front-end and back-end development.
  • Proficiency in Java frameworks (e.g., Spring Boot, Quarkus, Hibernate, or Mulesoft, etc.).
  • Proficiency in languages HTML, CSS, and JavaScript .
  • Proficiency in JavaScript frameworks (React, Angular, or Vue.js) .
  • Some knowledge of Databricks, Python, Spark, Scala, SQL, C++, and Java .
  • Experience with visualization libraries and CI/CD pipelines .
  • Experience working with RESTful APIs and handle asynchronous programming for smooth communication with backend systems, integration layer, services, data processing.
  • Awareness of visualization libraries (D3.js, Posit Connect, Plotly, Streamlit, Shiny, powerBI, Tableau, etc.) .


Relevant Certifications are advantageous:

  • Certifications in full-stack software development, system engineering, software architecture solutions frameworks, Information Systems Security Certificates. MLOps, and Machine Learning certificates are advantageous.
  • This is an excellent opportunity for the AI Apps Full Stack Software Developer to advance their career by working with cutting-edge technologies and driving business value. If you are passionate about leading AI/GenAI Apps optimization initiatives and have a proven track record in software architecture, we invite you to join our forward-thinking team at Mondelez International. Apply now to shape the future of our Data Science practices.

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