Description
[DT] : AI Technology Leader / Engineer
Location: Noida, India
Department: Operations
Experience: 3 to 12 Yrs
AI Technology Leader / Engineer
Responsibilities : AI Technology Leader
Lead a team of 3-10 Machine Learning Engineers.
Set and lead the strategic direction for AI/ML initiatives, identifying high-value opportunities and ensuring alignment with the company’s longterm business objectives and technology vision.
Lead the architecture, design, and drive end-to-end development process of scalable, production-grade machine learning systems that
deliver measurable business impact across multiple domains.
Influence and align cross-functional teams and executive stakeholders, serving as a trusted technical advisor and ensuring machine
learning efforts are integrated into broader product and platform strategies.
Provide technical leadership and mentorship for your team, guiding staff-level and senior engineers, cultivating a high-performance culture,
and elevating the overall technical bar of the organization.
Lead the evaluation and adaptation of cutting-edge research and open-source technologies, translating breakthroughs into practical,
deployable enterprise solutions.
Establish and govern technical standards for model development, evaluation, deployment, and monitoring, ensuring robustness,
reproducibility, and ethical AI practices.
Own the technical roadmap for ML infrastructure and tooling, driving long-term investments in platform capabilities that accelerate
experimentation and deployment velocity.
Shape organizational thinking through thought leadership, publishing internal whitepapers, presenting at technical forums, and influencing
the company’s external AI brand.
Prototype and champion innovative machine learning applications, delivering PoCs that communicate strategic value and inspire executive
buy-in.
Responsibilities : AI Technology Engineer
Architect, design, and oversee the development and deployment of cutting-edge machine learning models and algorithms to address high-impact
business challenges.
Drive collaboration across teams and departments, aligning machine learning initiatives with organizational goals and business priorities.
Provide technical leadership within the team by mentoring senior and junior engineers and fostering a culture of excellence in machine learning
and software development.
Lead the investigation, customization, and scaling of open-source machine learning frameworks for enterprise applications.
Define and implement standards for evaluating and selecting tools, frameworks, and platforms for various machine learning use cases.
Lead code reviews and enforce high-quality standards for the entire AI team.
Act as a technical advisor to stakeholders, translating complex machine learning concepts into actionable business insights and strategic
recommendations. E.g. Lead the creation of PoC (Proof of Concept) solutions, showcasing innovative machine learning applications to drive buyin from key stakeholders.
Contribute to the strategic vision of the AI team by driving innovation and shaping the roadmap for machine learning initiatives.
Requirements
B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical field, with 10+ years of industry experience delivering ML
solutions in production environments.
Strong programming skills in Python, along with hands-on experience using core data science libraries (e.g., NumPy, pandas, matplotlib).
Deep expertise in machine learning frameworks, including both deep learning (e.g., TensorFlow, PyTorch) and classical models (e.g., ScikitLearn).
Solid practical understanding of supervised and unsupervised learning, with experience applying techniques like classification, regression,
clustering, and forecasting.
Strong foundation in statistical methods and the ability to translate them into scalable ML solutions.
Proven ability to design and build robust, maintainable, and scalable codebases, with an engineering-first approach.
Experience driving cross-functional initiatives, mentoring other engineers, and setting technical direction for ML projects.
Excellent communication and collaboration skills, with a track record of effectively partnering with product, data, and business teams.
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