AI Developer | Onsite, Noida | Open to India-based candidates only

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Noida, Gautam Buddha Nagar, Uttar Pradesh, IND
In-Office
Junior
Professional Services • Consulting
Powering performance and unlocking potential worldwide. We lead in talent development and managed learning services.
The Role
As an AI Developer, you will design, develop, and deploy machine learning models, collaborate with teams, and ensure performance and quality in AI solutions.
Summary Generated by Built In
AI Developer | Onsite, Noida | Open to India-based candidates only

Position type: Full-time employee

Location: Onsite - Noida, India

Why this role exists
We are building AI solutions that solve real business problems, not demos or experiments that live on a slide. As an AI Developer on our team, you will design, build, deploy, and continuously improve production-ready AI and machine learning systems used by real users. This role is for someone who enjoys hands-on development, cares about quality and scalability, and wants to see their work move from idea to impact.

This is a full-time, onsite role based in our Noida office. You will work closely with engineers, data scientists, and product partners in a collaborative, fast-moving environment.

What you will do

Build and deliver AI solutions

  • Design, develop, and validate machine learning and deep learning models to address domain-specific business challenges

  • Work across a range of approaches including classical ML, NLP, computer vision, reinforcement learning, and transformer-based models

  • Apply Generative AI techniques, including working with large language models and retrieval-based systems, where appropriate

Data engineering and preparation

  • Collaborate with data scientists and engineers to source, clean, and preprocess large datasets

  • Perform feature engineering and data selection to improve model inputs and outcomes

Production deployment and MLOps

  • Deploy models into production environments that support real-time or near real-time use cases

  • Build and maintain MLOps pipelines for deployment, monitoring, versioning, and retraining

  • Use Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS, Azure, or GCP

  • Integrate models into applications through APIs or model-serving frameworks

Performance, quality, and improvement

  • Optimize models for performance, latency, scalability, and resource efficiency

  • Implement testing strategies including unit testing, regression testing, and A/B testing

  • Monitor model performance and improve solutions based on data, feedback, and usage patterns

Collaboration and communication

  • Work closely with cross-functional teams including engineering, product, and subject matter experts

  • Document model architectures, training processes, and experimental results

  • Communicate technical concepts clearly to both technical and non-technical stakeholders

Ethical and responsible AI

  • Contribute to ethical AI practices with attention to fairness, transparency, and accountability

  • Help identify and mitigate risks such as bias, hallucinations, or incorrect outputs

What we’re looking for

Required

  • Minimum 2 years of hands-on experience in AI or machine learning development

  • Strong proficiency in Python and experience with libraries such as TensorFlow, PyTorch, Keras, or Scikit-learn

  • Solid understanding of ML and DL architectures including CNNs, RNNs or LSTMs, and Transformers

  • Experience with data manipulation and analysis using Pandas, NumPy, and SciPy

  • Familiarity with software engineering best practices including Git, testing, and code optimization

  • Experience deploying models to cloud platforms or on-premise environments

  • Ability to work full-time from our Noida office

Preferred

  • Hands-on experience with large language models such as GPT, Claude, Mistral, or LLaMA

  • Experience with prompt engineering, Retrieval-Augmented Generation (RAG), or vector-based search

  • Familiarity with tools such as LangChain, LlamaIndex, Hugging Face, Pinecone, FAISS, or Weaviate

  • Experience with MLOps tools like MLflow, Kubeflow, or DVC

  • Exposure to applying AI in domains such as healthcare, finance, retail, manufacturing, or customer service

  • Strong grounding in statistics and optimization

Why join us

  • Work on real, production-grade AI systems with measurable business impact

  • Collaborate with experienced engineers and AI practitioners in a supportive, hands-on environment

  • Build breadth across models, tools, and deployment approaches while deepening your expertise

  • Be part of a team that values responsible, ethical AI and high-quality engineering

Ready to apply?
If you are excited to build AI systems that move beyond experimentation and into real-world use, we would love to hear from you. Apply now and tell us about the AI solutions you have built and want to build next.

Skills Required

  • Minimum 2 years of hands-on experience in AI or machine learning development
  • Strong proficiency in Python and experience with libraries such as TensorFlow, PyTorch, Keras, or Scikit-learn
  • Solid understanding of ML and DL architectures including CNNs, RNNs or LSTMs, and Transformers
  • Experience with data manipulation and analysis using Pandas, NumPy, and SciPy
  • Familiarity with software engineering best practices including Git, testing, and code optimization
  • Experience deploying models to cloud platforms or on-premise environments
  • Ability to work full-time from our Noida office
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The Company
HQ: Princeton, New Jersey
596 Employees
Year Founded: 1994

What We Do

Infopro Learning is an award-winning workforce transformation consultancy that unlocks the potential of people to power business performance. As a global leader in talent development and managed learning services, Infopro Learning offers solutions that support the entire lifecycle of learning, from strategy to talent sourcing. Our approach is anchored in innovation, agility, and a distinctive performance driven design that provides a clear, measurable roadmap for achieving organizational objectives and delivering quantifiable outcomes.

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