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SSIMRICSMLE01 – Senior Machine Learning Engineer

Location: Plainsboro Center, NJ, 08536, US
Reference ID:

We are looking for an expert machine learning and data science engineer who can provide the ML services to data scientists, create AI solutions, scale up the ML models, manage the ML Ops, and perform needed governance tasks around deployed models. This person will be the backbone of the AI ML CoE department and will work on new age GenAI solutions. This person should be open to learn and implement new relevant tools and use cases. This person should be able to create the complete solution, so full stack development skill with experience of visualization/UX/UI will help a lot. This person will work in SAFe agile framework, so should have knowledge around it. This person should be very good at communication and in a collaborative environment.

Responsibilities of the role are listed below but not limited to

• Provide ML services to data scientists, such as data preparation, feature engineering, model selection, optimization, deployment, and monitoring.

• Work closely with product SMEs, data scientists, and other stakeholders to understand the business requirements, use cases, and objectives of AI and ML initiatives.

• Design, develop, and deploy end-to-end AI and ML solutions using AWS services, Dataiku, Python, and other relevant technologies.

• Enable new features and capabilities of products into our AI and ML ecosystems, ensuring scalability, reliability, security, and performance.

• Scale up the ML models to handle large volumes of data and requests, using Dataiku and AWS services such as S3, EC2, Lambda, SageMaker, etc.

• Provide technical guidance and support to data scientists and other AI and ML users, facilitating knowledge sharing and collaboration.

• Manage the ML Ops, such as version control, testing, continuous integration, continuous delivery, continuous monitoring, troubleshooting of deployed ML models and pipelines.

• Learn and implement new relevant tools and use cases, such as Dataiku features, AWS AI services, ML frameworks, libraries, APIs, Azure AI stack etc.

• Create the complete solution, from data ingestion to user interface, using full stack development skills and experience of visualization/UX/UI.

• Communicate and collaborate effectively with stakeholders, such as business users, data scientists, developers, testers, etc.

• Integrate various data sources and platforms with our AI and ML platform, using best practices and standards.

• Create and maintain documentation, reports, and presentations on AI and ML projects and solutions.

• Perform governance and compliance tasks related to AI and ML, such as data quality, ethics, privacy, and auditability.

• Research and implement new and emerging tools, techniques, and trends in AI and ML, especially in the domain of GenAI.

• Work in a SAFe agile framework, following the principles and practices of agile development.


• Bachelor’s degree or higher in computer science, engineering, mathematics, statistics, or related field.

• At least 5 years of experience in machine learning and data science, with proven track record of delivering successful AI solutions.

• Expert level skill in Dataiku.

• Expert level skill in AWS services, such as S3, EC2, Lambda, SageMaker, etc.

• Proficient in Python, R, SQL, and other programming languages for data analysis and ML development.

• Familiar with ML frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Keras, Scikit-learn, Pandas, NumPy, etc.

• Knowledgeable in ML concepts, techniques, and algorithms, such as supervised learning, unsupervised learning, deep learning, etc.

• Experienced in full stack development, with skills in web development, visualization, UX/UI, etc.

• Proficient in various ML best practices, standards, and methodologies, such as SAFe agile, ML Ops, ML governance, etc.

• Expert in Azure and other cloud platforms, and willingness to learn and adapt to new technologies.

• Excellent communication and collaboration skills, with ability to explain complex technical concepts to non-technical audiences.

• Strong problem-solving and analytical skills, with attention to detail and quality.

• Curious and passionate about learning new things and exploring new possibilities in AI and ML.

Requirement summary:

1. Behaviour requirement

• Fast learner

• Collaborative nature

• Share knowledge with everyone and always eager to teach or uplift other skills, if provided opportunities

• Structured person

• Solution oriented person

• Good documentation practices

• Confident to speak with data scientists and help them in solving day to day challenge on data science.

• Confident to speak with data engineers and help them in solving day to day challenge.

• Confident speaker to present solution in business language.

• Professional and respectful attitude.

• Be able to read the shared material (I.e. Blogs) and quick to create quick PoC.

• Proactive: – Be persistence to gain access or information and don’t just keep waiting for another team to respond

2. Process requirements

• Understand SAFe Agile setup!

• Experience in envisioning AI product, divide it into features and then guide small team to divide further into user stories.

• Technology and Solution Architecture experience

• Experience with visualisation and UI/UX will be preferred.

3. Technology Requirement

• Data Science and Machine Learning – Expert

• AWS eco-system – Expert

• Dataiku – Expert

• Deployment model – Expert

• Governance of Models after deployment – expert

• Operations and support matrix for production models – expert

• Experienced in GenAI and keep up with recent development – experienced in using LLMs/GenAI, creating solutions and hosting as well as training LLMs.

• Explorer to CI/CD – Expert

• Experienced in full stack – good exposure with some experience.

• Experienced in Azure AI technology stack – to use OpenAI

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