AI LLM Technology Architecture Manager

About The Role
Skill required: Tech for Operations - Artificial Intelligence (AI)
Designation: AI LLM Technology Architecture Manager
**Qualifications:**Any Graduation
**Years of Experience:**13 to 18 years

What would you do The role of an ML Research Engineers is both strategic and hands-on, blending deep technical expertise with creative problem-solving. In this position, you will lead the exploration and application of advanced artificial intelligence methodologies, focusing on pushing the boundaries of what is possible with data-driven insights. Your background in engineering or science, complemented by a decade or more of experience, will enable you to devise and execute research agendas that align with organizational goals. You will collaborate closely with multidisciplinary teams to conceptualize, prototype, and scale AI solutions tailored to complex, real-world challenges. This includes formulating research hypotheses, designing experimental frameworks, and validating innovative algorithms across domains such as Natural Language Processing, Computer Visionand Deep Learning. ML Research Engineers are expected to stay abreast of emerging trends, contribute to scholarly publications, and translate theoretical advances into practical business impact. Demonstrating strong communication skills, you will effectively articulate research outcomes to both technical and non-technical stakeholders. Your role will also involve mentoring junior researchers, fostering a culture of intellectual curiosity, and ensuring rigor in all research activities.
What are we looking for To excel in this role, an ML Research Engineers should possess a strong combination of technical, analytical, and interpersonal skills, including:Lead and contribute to research initiatives at the intersection of cognition, behaviour, and technology, Design, implement, and analyse experimental studies to explore cognitive functions, behavioural responses, and their underlying neural or psychological mechanisms using AI/ML/Generative AI Utilize advanced quantitative and qualitative methods to interpret complex human data, including surveys, experiments, biometric or observational datasets. Stay abreast of the latest developments in cognitive science Translate theoretical insights into actionable strategies for enhancing user experience, improving product usability, or driving positive behaviour change within organizational or consumer contexts. Effectively communicate research findings and implications to both technical and non-technical stakeholders, Mentor and guide junior scientists and researchers, fostering a culture of intellectual curiosity, ethical rigor, and continuous learning. Demonstrate a strong track record in managing multiple projects and stakeholders Showcase adaptability, critical thinking,
Roles and Responsibilities: Lead ML research initiatives Design and implement experimental studies Analyse cognitive and behavioural data Apply AI/ML to human research Interpret quantitative and qualitative findings Translate insights into actionable strategies Communicate results to stakeholders effectively Mentor and guide junior researchers Manage multiple projects and stakeholders Foster a culture of continuous learning Demonstrate critical thinking and adaptability Navigate complex, real-world organizational challenges .
QualificationAny Graduation