Senior Manager Applied Science
At a glance
Senior AI Research role at Weekday AI. Bengaluru · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Lead and mentor applied scientists, set their development paths, and establish standards for research, code quality, and technical work
- Coordinate with product and customer success teams to rank customer needs, adjust plans, and agree on delivery expectations
- Guide R&D and product plans, connecting machine learning work to business goals and customer priorities
- Set technical direction for scalable AI/ML systems and oversee data, model training, validation, deployment, and monitoring
- Promote model compression, quantization, and distributed training while improving team workflows and delivery practices
What you bring
- At least twelve years of hands-on analytics, data science, and deep learning work in business-critical settings
- At least three years managing teams of five or more, preferably in applied science or cross-functional work
- A bachelor's, master's, Ph.D., or related-field qualification in a listed quantitative discipline
- Strong machine learning, deep learning, and explainable AI skills, with the ability to explain technical ideas to non-technical stakeholders
- Hands-on Python and SQL skills, plus experience building and deploying ML models for specific business needs
Who this fits
This is a senior people-lead role for someone who can manage applied scientists while guiding technical delivery and customer-facing work. The position is based onsite in Bengaluru.
From the employer
This role is for one of Weekday’s clients
Salary range: Rs 7000000 - Rs 12000000 (ie INR 70 - 120 LPA)
Min Experience: 14+ years
Location: Bengaluru
JobType: full-time
We are seeking a passionate and dynamic Senior Manager of Applied Science to lead a team of applied scientists focused on building next-generation AI applications on the cloud. You will work closely with product, business, machine learning engineering, and customer success teams to align priorities, timelines, and deliverables. You will drive AI/ML development efforts and ensure customer engagements are supported with high-quality, scalable solutions that deliver measurable impact.
Requirements
Key Responsibilities
Leadership and Team Management
- Lead, mentor, and manage a team of applied scientists, including senior scientists and team leads.
- Build and scale a high-performing team of 5-8 scientists; provide regular mentoring and establish clear career development paths.
- Set and promote best practices for research, development, code quality, and technical excellence
Customer Engagement & Deliverable Management
- Collaborate with product and customer success teams to prioritize customer needs and align development timelines accordingly.
- Integrate customer feedback into development cycles, adapting priorities as business needs evolve.
- Act as the technical point of contact for customer engagements, setting clear expectations for deliverables and timelines.
- Ensure high-quality, on-time delivery of customer-facing AI/ML products that meet or exceed expectations.
Product Development & Strategy
- Lead the execution of the R&D and product roadmap, aligning ML initiatives with business goals and customer priorities.
- Drive product strategy in collaboration with product management, business development, and operations.
- Provide architectural and technical leadership on key projects, ensuring robustness, scalability, and flexibility.
Scalability & Best Practices
- Foster a high-performing team through agile workflows, continuous improvement, and strong delivery processes.
- Architect and implement scalable AI/ML solutions aligned with ASD's long-term vision, using cloud-native technologies and microservices.
- Oversee the full ML lifecycle-including data collection, model training, validation, deployment, and monitoring-ensuring effective team collaboration and resource management.
- Promote advanced techniques such as model compression, quantization, and distributed training.
- Champion industry best practices in development to ensure code quality, performance, and scalability.
- Stay current with advancements in ML and lead team engagement in the broader scientific community.
- Collaborate with design, product, and engineering teams to deliver high-performance solutions in a fast-evolving environment.
Required Qualifications
- Bachelor’s, Master’s, or Ph.D. in Data Science, Mathematics, Operations Research, Applied Mathematics, Computational Science, or a related field.
- Strong foundation in probability, statistics, and scientific problem-solving.
- 12+ years of hands-on experience in analytics, data science, and deep learning in business-critical environments.
- 3+ years of experience managing teams of 5 or more, preferably in applied science or cross-functional settings..
- Proven track record of delivering high-impact, data-driven solutions to complex business problems.
- Proficient in machine learning, deep learning, and explainable AI techniques, with the ability to communicate technical concepts to non-technical stakeholders.
- Experience developing and deploying state-of-the-art ML models tailored to specific business needs.
- Strong programming skills in Python and SQL; experience with feature engineering and deep learning pipelines.
- Familiarity with deep learning frameworks such as TensorFlow, Keras, and PyTorch.
- Experience with computer vision (e.g., OpenCV) and natural language processing (e.g., spaCy).
- Skilled in the Design of Experiments for scientific testing and optimization.
- Proficient in Git for version control and collaboration.
- Working knowledge of cloud platforms such as AWS, GCP, and Azure.
- Strong analytical thinking and structured problem-solving abilities.
- Excellent communication and collaboration skills in cross-functional teams.
Preferred Qualifications
- Demonstrated leadership experience in mentoring junior engineers and managing cross-functional projects.
- Proven innovation track record—solutions that delivered significant business impact or led to patents.
- Self-motivated, proactive problem-solver with strong project ownership.
- Domain knowledge or experience in recommendation systems, NLP, or computer vision.
- Strong collaboration skills across multiple teams, with an ability to manage conflict and align priorities.
Good-to-have skills
Applied Sciences, Senior Manager, recommendations