Machine Learning Engineer – Ready to accelerate your professional growth in artificial intelligence? Wipro is expanding its high-velocity team and looking for driven engineers to build the future of AI. This is a full time opportunity and based in Bengaluru and offering The Good CTC. Access the full article for detailed insights and connect on LinkedIn for further updates.
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About the Wipro Company
Wipro is the leading IT and Technology services related company focused on building innovative solutions that address clients to transform most complex digital transformation needs. Wipro helps clients realize their boldest ambitions and establish future ready, sustainable businesses. With more than 23,0000 employees and business partners across 65 countries. Wipro delivers on the promise of helping our customers, colleagues and communities thrive in an ever changing world.
- Role : Machine Learning Engineer
- Location : Bengaluru
- Employee Type : Full Time , Permanent
- Department : Artificial Intelligence and Machine Learning
- Experience : 3 – 5 Years
- CTC – Not Mentioned
- Link to Apply – Wipro – Machine Learning Engineer
Job Highlights for Machine Learning Engineer
- Undergraduate or advanced degree in Computer Science, Data Science, or a closely related technical discipline qualification from a well-known institute.
- Automated screening tools and artificial intelligence may be utilized during our recruitment process to assess resumes, parse applications, and analyze candidate submissions.
- Seeking applicants who possess 3 to 5 years of professional experience in a directly related role.
- Candidates must play a crucial role in developing and implementing AI/ML solutions within our organizations.
- Applicants expertise will contribute to the successful deployment of AI models, enhancing business outcomes and driving innovation in the AI/ML domain.
- Strong foundational knowledge of computational finance, algorithmic accounting, and quantitative financial structures.
- Proven capability to design, build, and deploy ML algorithms that automate credit risk assessment and synthesize financial intelligence reports.
Job Description for Machine Learning Engineer
- Engineer predictive features and anomaly detection models to flag critical loan vulnerabilities, contractual breach risks, and early-warning distress indicators.
- Develop Natural Language Generation (NLG) or automated pipeline workflows to synthesize complex model outputs into concise, executive-ready risk intelligence summaries.
- Design and scrape multi-source data architectures to ingest comprehensive macroeconomic trends, competitive market dynamics, and industry-specific risk vectors.
- Collaborate with cross-functional stakeholders and clients to systematically clean dataset anomalies, ingest missing variables, and validate algorithmic model assumptions.
- Applicants must know to design and implement AI/ML reference architecture assets and solutions.
- Deployed and managed AI/ML tools, platforms and infrastructure effectively.
- Implement ethical AI practices and governance standards.
- Track and assess artificial intelligence deployments to quantify and validate business value and ROI.
- Architect, train, and productionise machine learning architectures and end-to-end models.
- Partner with client stakeholders, contribute to Request for Proposal (RFP) cycles, and design customized AI strategies.
- Engineered modular pipelines, reusable code methodologies, and scalable baseline models to optimize team efficiency.
- Operate fluently across diverse cloud environments utilizing container systems like Docker and Kubernetes.
- Write production-grade code using software languages such as Python, R, Scala, and MATLAB.
- Solve complex problems across Generative AI applications, Computer Vision systems, NLP frameworks, and Predictive Modeling.
Desired Skill for Machine Learning Engineer
- Seeking applicants who possess 3 to 5 years of professional experience in a directly related role.
- Undergraduate or advanced degree in Computer Science, Data Science, or a closely related technical discipline is mandatory.
- Strong interpersonal and verbal skills to interface confidently with debt management leads, external partners, and internal business pillars.
- Demonstrated track record of being self-motivated, versatile, inventive, and highly accountable within highly collaborative team structures.
- Possesses strong business acumen with a grounded, practical approach to solving operational problems.
- Exhibits high resilience and a comfort level with navigating ambiguity in fluid, high-velocity corporate cultures.
- 3–5 years of professional experience in artificial intelligence and machine learning, with a heavy emphasis on end-to-end model development and deployment.
- Strong programming agility in software languages such as Python, R, Scala, and scientific computing frameworks like MATLAB.
- Direct engineering experience with Enterprise Chatbots, LLMs, RAG frameworks, Agentic AI systems, and vector databases.
- Demonstrated troubleshooting skills across core domains like Generative AI, Computer Vision, and advanced NLP.
- Solid familiarity with modern MLOps methodologies, automated deployment pipelines, and model orchestration workflows.
- Ability to interface effectively within cross-functional teams to drive collective product goals.
- Articulate presentation skills to guide, inspire, and translate complex technical frameworks for diverse audiences.
- An undergraduate or advanced degree (B.S./M.S.) in Computer Science, Data Science, or a closely related quantitative discipline.
- Prior success developing advanced Generative AI applications, intelligent workplace agents, or automated content solutions.
- Operational familiarity with hosting environments across public cloud platforms, secure on-premises hardware, and hybrid architectures.
- Practical knowledge of virtualization and container management tools, specifically Docker and Kubernetes.
- Active involvement in sales engineering, authoring RFP responses, client consulting, and full-lifecycle AI project delivery.
Read More | KPMG – AI Engineer-Associate Consultant
Education
- UG: Any Graduate
- PG: Any Postgraduate
Skills for Machine Learning Engineer
- Stress testing
- Machine Learning
- Artificial Intelligence
- Python
- R
- Scala
- Matlab
- Version control tools
- Kubernetes
- Data science
- Monitoring
- Recruiting
- Analytics analyst
Additional responsibilities for Machine Learning Engineer
- Demand Generation & Solution Development
- Go-To-Market Support: Partner with sales, pre-sales, and consulting teams to architect proactive solutions that stimulate market demand.
- Proof of Concepts: Build functional prototypes aligned with core offerings to enable solution-led sales cycles.
- Academic Alliances: Collaborate with universities for campus recruitment, collaborative research, and data science training.
- 2. Revenue Generation via AI/ML Deployment
- Model Engineering: Develop ML/DL frameworks to automate workflows and optimize business decision-making.
- Performance Management: Embed real-time model monitoring and observability tools directly into production infrastructure.
- 3. Team & Performance Management
- Talent Acquisition: Support technical screening and interviews to onboard highly qualified team members.
- Performance Evaluation: Conduct objective appraisals, deliver constructive feedback, and model core company values and processes.
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