Large Language Model

2 weeks ago

Pune, Maharashtra, India F337 Deutsche India Private Limited, Pune Branch Full time
:


At the "Service Solutions and AI" Tribe, our mission is to revolutionize our Private Bank process landscape by implementing holistic, front-to-back process automation.

We are committed to enhancing efficiency, agility, and innovation, with a keen focus on aligning every step of our process with the customer's needs and expectations.

Our dedication extends to driving innovative technologies, such as AI & workflow services, to foster continuous improvement.

We aim to deliver 'best in class' solutions across products, channels, brands, and regions, thereby transforming the way we serve our customers and setting new benchmarks in the industry.

As a Large Language Model (LLM) Engineer, your role is pivotal in the development of intelligent systems that can understand, generate, and respond to human language effectively.

Your key responsibilities include developing and refining large language models, collaborating with data scientists and machine learning engineers, and implementing machine learning algorithms and statistical methods.

You will also analyze large datasets to identify patterns and trends, evaluate the performance of the language model, and troubleshoot any issues that arise during the development and deployment of the model.

Staying updated on the latest advancements in AI, machine learning, and natural language processing is also a crucial part of your role.

Remember, your work significantly contributes to advancements in AI and its applications across various sectors.
Join us in our journey to redefine banking with AI and service solutions into the future.

What we'll offer youAs part of our flexible scheme, here are just some of the benefits that you'll enjoyBest in class leave policyGender neutral parental leaves100% reimbursement under childcare assistance benefit (gender neutral)Sponsorship for Industry relevant certifications and educationEmployee Assistance Program for you and your family membersComprehensive Hospitalization Insurance for you and your dependentsAccident and Term life InsuranceComplementary Health screening for 35 yrs.

and aboveYour key responsibilitiesAI and ML Implementation:

You will work in the Service Delivery and AI tribe domain to implement AI and ML applications. This involves understanding the business context, identifying opportunities for AI integration, and deploying solutions that drive efficiency and innovation.

Business Requirement Analysis:

You will translate business requirements into technical concepts. This involves understanding the business needs, defining clear AI objectives, and designing AI solutions that align with these objectives.

ML System Design:

You will design machine learning systems and self-running AI software to automate predictive models. This involves creating robust and scalable ML architectures that can process large datasets and generate accurate predictions.

Model Evaluation:

You evaluate the performance of the language model using appropriate metrics and techniques. This includes conducting A/B tests, analyzing error rates, and making necessary adjustments to the model.

Troubleshooting:

You troubleshoot any issues that arise during the development and deployment of the language model. This includes debugging code, resolving technical issues, and ensuring the model performs optimally in different environments.

Algorithm Research and Implementation:

You will research and implement suitable ML algorithms and tools.

This involves staying updated with the latest ML research, selecting the most effective algorithms for the task, and customizing them as needed.

Data Processing:

You will transform unstructured data into useful information using techniques like Natural Language Processing (NLP). This involves developing algorithms to extract meaningful insights from raw data.
Data Science Experiments

:

You will execute data science experiments to gain new insights into the available data. This involves designing and conducting experiments, analyzing the results, and using these insights to generate new business opportunities.
Data Visualization

:

You will visualize data using common Business Intelligence (BI) tools. This involves creating intuitive and interactive dashboards that allow stakeholders to easily understand the data.
Data Pre-processing

:

You will perform advanced pre-processing of data as required by the respective AI application. This involves cleaning, transforming, and normalizing data to ensure it is suitable for the ML models.

System Training:

You will train and retrain LLM systems when necessary.

This involves updating the ML models with new data, tuning the parameters, and retraining the models to ensure they remain accurate and effective.

ML Libraries and Frameworks Extension

:

You will extend existing ML libraries and frameworks if necessary. This involves adding new functionalities to the libraries and frameworks to meet specific needs.
Regulatory Compliance

:

You will roll out and document changes and applications according to regulatory requirements. This involves ensuring all AI applications comply with relevant laws and regulations, and maintaining detailed documentation for audit purposes. This includes respecting user privacy, avoiding bias in the model, and ensuring the model is used responsibly.

Maintenance and Bugfixes:

You will maintain and deliver bugfixes for existing AI and ML applications. This involves monitoring the applications, identifying and fixing bugs, and ensuring the applications remain reliable and efficient.
Collaboration and Communication

:

You will work closely with other teams, including data engineers, business analysts, and IT teams, to ensure the successful implementation of AI and ML projects.

This involves clear communication, collaboration, and knowledge sharing.
Continuous Learning and Improvement

:

You will stay updated with the latest developments in AI and ML, and continuously improve your skills and knowledge.

This involves attending workshops, reading research papers, and seeking feedback for improvement.

Your skills and experienceMandatory Skills and Qualifications:

Educational Background:

A Bachelor's Degree in Computer Science or a similar field is required. A Master's degree is a plus.

Experience:

Proven experience as a Machine Learning Engineer or a similar role is crucial.

Knowledge of ML Frameworks and Libraries:

Extensive knowledge of machine learning frameworks, libraries, data structures, data modeling, and software architecture is essential.

Mathematical Proficiency:

In-depth knowledge of mathematics, statistics, and algorithms is necessary.

Coding Skills:

Ability to write robust code in Python and, if necessary, R.

Python Frameworks:


Knowledge of common Python frameworks in the area of data processing, data science, and machine learning such as Pandas, Scikit-Learn, Numpy, Tensorflow, and others.

Data Visualization:

Experience with visualizing data in tools like Tableau, Looker, or Qlik Sense.

Communication Skills:

Excellent communication skills are required to effectively collaborate with team members and stakeholders.

Teamwork:

Ability to work in a team is crucial.

Analytical and Problem-Solving Skills:

Outstanding analytical and problem-solving skills are necessary to troubleshoot issues and optimize solutions.

Work Ethic:

A structured and intrinsically motivated way of working is important.

Adaptability:

Capability to work in a fast-paced and changing environment is essential
Optional Skills and Qualifications:

Vertex AI in GCP:

Experience in the Vertex AI in Google Cloud Platform (GCP) is a plus.

Low Code Data Science Tools:

First experience with low code Data Science tools such as Kubeflow is beneficial.
How we'll support youTraining and development to help you excel in your careerCoaching and support from experts in your teamA culture of continuous learning to aid progressionA range of flexible benefits that you can tailor to suit your needs

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