Who is a AI / ML Engineer?
A technological specialist who creates, develops, and implements systems that allow machines to learn from data and make wise judgments is known as an AI/ML engineer. They develop models that can identify trends, forecast results, or automate processes using methods from artificial intelligence and machine learning. Typically, they prepare datasets, choose algorithms, train and test models, and incorporate these models into services or applications. In order to guarantee accuracy, dependability, and efficiency in practical settings, AI/ML engineers also track model performance and make system improvements over time.
Basic Skills Required to be a AI / ML Engineer
A person must have a solid background in programming, mathematics, and data analysis in order to work as an AI/ML engineer. Building and testing models requires proficiency in languages like Python or Java. Designing systems that learn from data is made easier with an understanding of machine learning and artificial intelligence ideas. Accurate model development also requires an understanding of probability, linear algebra, and statistics. It is crucial to be familiar with data processing, algorithms, and model evaluation methods. Reliable AI systems also require logical reasoning, problem-solving skills, and familiarity with the frameworks and tools used to create intelligent applications.
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Basic Knowledge Required to be a AI / ML Engineer
A person must have a foundational understanding of programming, mathematics, and data processing in order to work as an AI/ML engineer. It is easier to develop and evaluate intelligent systems when one is familiar with programming languages like Python or Java. Accurate model development requires an understanding of mathematical topics like probability, statistics, and linear algebra. Designing systems that can learn from data and make predictions also requires a thorough grasp of machine learning and artificial intelligence ideas. Additionally, preparing datasets and enhancing machine learning model performance are made easier with a fundamental understanding of algorithms, data structures, and data preprocessing.
Job Market in Bangalore for AI / ML Engineer
Bangalore is a large technology hub with numerous multinational corporations, startups, and research facilities, making the job market for AI/ML engineers there robust. Large organizations such as Google, Microsoft, and Amazon run major AI development teams there. Professionals in AI and machine learning are in high demand, and job postings for these positions have grown dramatically in recent years. Additionally, Bangalore is home to numerous businesses and innovation hubs that focus on intelligent systems, automation, and data science. The city provides several career prospects for qualified AI/ML engineers due to its robust technology environment and investment in AI research.
Growth in Bangalore as a AI / ML Engineer
Because Bangalore is a significant hub for technology businesses, startups, and research institutions, career growth for AI/ML engineers is thought to be quite robust. Artificial intelligence and machine learning are being used more and more by a variety of industries, including automation, healthcare, finance, and e-commerce, to enhance their offerings. This gives engineers ongoing chances to grow into more senior positions, such as research expert, AI architect, or senior engineer. Bangalore is one of the greatest locations in the nation for long-term career development and innovation in AI-related disciplines since it is home to a sizable portion of India's AI talent and job postings.
Job Description
- Project Role: AI / ML Engineer
- Project Role Description: Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
- Must have skills: Microsoft Azure Architecture
- Minimum 7.5 year(s) of experience is required
- Educational Qualification: 15 years full time education
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Summary
As an AI/ML Engineer, you will work on creating systems and apps that make use of cloud AI services and artificial intelligence tools. Designing and developing application pipelines that are ready for production while maintaining high standards of quality will be your daily task. Additionally, you will investigate how generative AI models can be included into solutions, which could include a variety of cutting-edge technologies like deep learning, neural networks, chatbots, and image processing. To guarantee that the solutions created are efficient and satisfy the demands of the company, cooperation with cross-functional teams will be crucial.
Roles & Responsibilities
- Expected to be an SME.
- Collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Mentor junior team members to enhance their skills and knowledge.
- Continuously evaluate and improve existing processes and workflows.
Professional & Technical Skills
- Must To Have Skills: Proficiency in Python on Azure, LangChain, Langraph.
- Good To Have Skills: Experience with machine learning frameworks such as TensorFlow or PyTorch, Implementation of LLM
- Azure cloud eco-system (ADO, ADF, Databricks, SQL Server, delta tables, unity catalog, Vnet-subnet, Private endpoints, webapp, function app, containerization etc),
- Strong understanding of cloud computing concepts and services.
- Experience in developing and deploying AI models in production environments.
- Familiarity with data processing and analysis tools.
Additional Information
- The candidate should have minimum 7.5 years of experience in Python on Azure.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
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Work Life of a AI / ML Engineer
An AI/ML engineer's job is to design, construct, and enhance data-driven learning systems. They gather and prepare datasets, create algorithms, train models, and evaluate their performance on a normal day. They use ideas from machine learning and artificial intelligence to address practical issues including automation, prediction, and recommendation. In order to incorporate models into applications, AI/ML engineers also work with product teams, data scientists, and software developers. Monitoring models, correcting mistakes, and updating systems to maintain accuracy and efficiency are all part of their job. The rapid evolution of AI techniques and technology makes continuous learning crucial.