Sobre este puesto de AI Solutions en Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฏ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฏ๐ฌ-๐ญ๐ฌ๐ฌ ๐๐ฃ๐)
Experience: 5+ yrs
Location: Gurgaon, Haryana, India, Delhi, India, Noida, Uttar Pradesh, India
Job Type: Full-time
We are seeking an experiencedย AI Solutions Engineerย to design, develop, and implement enterprise-grade Artificial Intelligence and Machine Learning solutions that solve complex business challenges and accelerate digital transformation. This role is ideal for professionals with strong expertise in AI, Machine Learning, data-driven decision-making, and scalable solution architecture who are passionate about delivering innovative, production-ready AI applications.
As an AI Solutions Engineer, you will collaborate with business stakeholders, product managers, data scientists, and engineering teams to transform business requirements into intelligent solutions. You will be responsible for developing end-to-end AI systems, integrating machine learning models into enterprise applications, optimizing model performance, and ensuring scalable, secure, and reliable deployments. This role offers the opportunity to work with cutting-edge AI technologies, large-scale datasets, and modern cloud platforms while driving innovation across multiple business domains.
Requirements
Key Responsibilities
- Design, develop, and deploy scalable AI and Machine Learning solutions that address business and operational challenges.
- Build, train, evaluate, and optimize machine learning and deep learning models for production environments.
- Collaborate with business stakeholders to understand requirements and translate them into AI-driven solutions.
- Develop end-to-end AI pipelines, including data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
- Integrate AI and ML models into enterprise applications, APIs, and cloud-based platforms.
- Evaluate emerging AI technologies, frameworks, and tools to recommend innovative solutions and best practices.
- Optimize model accuracy, scalability, latency, and overall system performance through continuous experimentation and improvement.
- Work closely with data engineering teams to ensure high-quality, reliable, and scalable data pipelines for AI workloads.
- Implement responsible AI practices, model governance, security, and compliance throughout the AI lifecycle.
- Monitor deployed models, analyze performance metrics, troubleshoot issues, and implement continuous model improvements.
- Contribute to technical architecture, documentation, code reviews, and knowledge sharing across engineering teams.
- Stay current with advancements in Artificial Intelligence, Machine Learning, Generative AI, and MLOps to continuously improve solution capabilities.
What Makes You a Great Fit
- 5+ years of experience inย Artificial Intelligence,ย Machine Learning, or advanced analytics solution development.
- Strong expertise in Machine Learning algorithms, deep learning techniques, and AI model development.
- Hands-on experience with Python and popular AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.
- Experience designing and deploying production-grade AI solutions on cloud platforms such as AWS, Azure, or Google Cloud.
- Strong understanding of data engineering, feature engineering, model evaluation, and MLOps best practices.
- Experience developing REST APIs and integrating AI models into enterprise applications and business workflows.
- Solid understanding of statistics, data structures, algorithms, and software engineering principles.
- Familiarity with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, or AI agents is highly desirable.
- Excellent analytical, problem-solving, and communication skills with the ability to explain complex AI concepts to technical and business stakeholders.
- Self-driven, innovative, and passionate about building scalable AI solutions that create measurable business impact while mentoring teams and driving technical excellence.