This position is an exciting opportunity with a growing IT team. Black Box Network Services is a leading communications system integrator dedicated to designing, sourcing, implementing, and maintaining today's complex communications solutions. This position is for a Data Scientist/AI Engineer that can deliver AI products that solve specific business problems by translating business needs into actionable requirements and managing iterative development processes.
Job Location: Manyata Tech Park, Bangalore
Role Summary
Responsible for analyzing large-scale data sets, building predictive models, and generating actionable insights using Microsoft SQL, Python, and Azure technologies.
Work closely with data engineers, and business stakeholders to understand the business requirements and deliver solutions that meet or exceed their expectations.
Ensure data quality, security, and compliance with best practices and standards.
Model Development & Optimization
Build and optimize ML models (e.g., supervised, unsupervised, reinforcement learning) for business needs. Collaborate with Al Architects to ensure alignment with overall Al architecture and best practices.Data Pipeline & Preprocessing
Work with the Solution Architect and Al Ops Engineer to design and maintain data pipelines. Preprocess large datasets and implement feature engineering techniquesModel Deployment & Monitoring
Collaborate with Al Ops Engineers to deploy and monitor models in production. Ensure models perform optimally and are retrained based on evolving needs.Cross Functional Collaboration
Partner with UI/UX Designers to ensure Al solutions provide an intuitive user experience. Work with Full Stack Developers to integrate Al models into front-end and back-end systems. Engage with QA Engineers to validate model accuracy and robustness through testing protocols.Innovation & AI Research
Stay updated on the latest Al/ML advancements (NLP, GenAl). Experiment with new techniques to solve complex business challenges.AI Governance & Ethical AI
Ensure Al models meet ethical standards, avoid bias, and comply with data privacy regulations
Required Skills
Expertise in machine learning, deep learning, and Al frameworks (e.g., TensorFIow, PyTorch, scikit-learn). Proficient in working with large datasets, data preprocessing, feature engineering, and data pipeline management. Experience with cloud environments (AWS, Azure, Google Cloud) and Al tools for scalable Al solutions. Hands-on experience in deploying models into production, model monitoring, versioning, and lifecycle management. Strong ability to work with Al Architects, Al Ops Engineers, Solution Architects, UI/UX Designers, Full Stack Developers, and QA Engineers in a cross-functional setting. Proficiency in Python or R, with knowledge of SQL and other data processing languages. Ability to stay current with evolving Al technologies and apply innovative solutions to complex problems.Desired Skills
Experience working with advanced Generative Al models (e.g., GPT, BERT, DALL-E) for specialized tasks. Expertise in Natural Language Processing or Computer Vision for domain-specific applications. Familiarity with AIOps/MLOps practices for streamlining Al model workflows and ensuring robust deployment in production environments. Understanding of Al governance, ethics, and bias mitigation strategies to ensure responsible Al development.Black Box is a leading technology solutions provider. Our mission is to accelerate our customers’ business by valuing relationships with our team members, clients and stakeholders. By continuously growing our knowledge, we remain relevant in the market and are in a superior position to help customers design, deploy and manage their IT infrastructure. Through our values, such as innovation, ownership, transparency, respect and open-mindedness, we deliver high-value products and services through our global presence and 2,500+ team members in 24 countries and growing. Black Box is a wholly-owned subsidiary of AGC Networks.
Black Box is an equal opportunity employer. Black Box does not discriminate against individuals on the basis of race, color, marital status, sex, sexual orientation, gender identity, religion, national origin, age, disability, veteran status, genetic information, or any other protected status, and endorses those policies and practices which seek to recruit, hire, train and promote the most qualified persons into available jobs.