Job Description

As an AI/ML Engineer, you’ll play a pivotal role in creating and delivering cutting-edge enterprise applications and automations using Infor’s AI, RPA technology. Your mission will be to identify innovative use cases, develop proof of concepts (PoCs), and deliver enterprise automation solutions that elevate workforce productivity and improve business performance for our customers.

A Day in The Life Typically Includes: 

·       Use Case Identification: Dive deep into customer, business requirements and business challenges. Identify innovative use cases that can be addressed through AI/ML solutions.

·       Data Insights: Perform exploratory data analysis on large and complex datasets. Assess data quality, extract insights, and share findings.

·       Data Preparation: Gather relevant datasets for training and testing. Clean, preprocess, and augment data to ensure suitability for AI tasks.

·       Model Development: Train and fine-tune AI/ML models. Evaluate performance using appropriate metrics and benchmarks, optimizing for efficiency.

·       Integration and Deployment: Collaborate with software engineers and developers to seamlessly integrate AI/ML models into enterprise systems and applications. Handle production deployment challenges.

·       Continuous Improvement: Evaluate and enhance the performance and capabilities of deployed AI products. Monitor user feedback and iterate on models and algorithms to address limitations and enhance user experience.

·       Proof of Concepts (PoCs): Develop PoCs to validate the feasibility and effectiveness of proposed solutions. Showcase the art of the possible to our clients.

·       Collaboration with Development Teams: Work closely with development teams on new use cases.

·       Best Practices and Requirements: Collaborate with team members to determine best practices and requirements.

·       Innovation: Contribute to our efforts in enterprise automation and cloud innovation.

Basic Qualifications: 

·       Experience: A minimum 2-3 years of hands-on experience in implementing AI/ML models in enterprise systems.

·       AI/ML Concepts: In-depth understanding of supervised and unsupervised learning, reinforcement learning, deep learning, and probabilistic models.

·       Programming Languages: Proficiency in Python or R, along with querying languages like SQL.

·       Data Handling: Ability to work with large datasets, perform data preprocessing, and wrangle data effectively.

·       Cloud Infrastructure: Experience with AWS Services and ML services for implementing ML solutions is highly preferred.

·       Frameworks and Libraries: Familiarity with scikit-learn, Keras, TensorFlow, PyTorch, or NLTK is a plus.

·       Analytical Skills: Strong critical thinking abilities to identify problems, formulate hypotheses, and design experiments.

·       Business Process Understanding: Good understanding of business processes and how they can be automated

·       Domain Expertise: Familiarity with Demand Forecasting, Anomaly Detection, Pricing, Recommendation, or Analytics solutions.

·       Global Project Experience: Proven track record of working with global customers on multiple projects.

·       Customer Interaction: Experience facing customers and understanding their needs.

·       Communication Skills: Excellent verbal and written communication skills.

·       Analytical Mindset: Strong analytical and problem-solving skills.

·       Collaboration: Ability to work independently and collaboratively.

·       Educational Background: Bachelor’s or master’s degree in computer science, Mathematics, Statistics, or a related field.

·       Specialization: Coursework or specialization in AI, ML, Statistics & Probability, Deep Learning, Computer Vision, or NLP/NLU is advantageous.

·       Data Analysis and Interpretation: Conduct in-depth analysis of historical data and trends to identify patterns, correlations, and anomalies that can inform future business strategies.

·       Documentation and Communication: Program and write maintainable and well-documented code and write summaries and reports to present technical findings/conclusions and project status updates.

·       Intelligent, fast-thinking and highly motivated with a strong problem-solving and analytical skills.

·       Experience with prompt engineering techniques, LLM finetuning and familiarity with LLM-based workflows/architectures such as retrieval-augmented generation.

·       Experience with Python (NumPy, Pandas, etc) must have experience in at least one of the common LLM toolkits, etc.,

·       SQL for databases querying.

·       Clear knowledge of a variety of machine learning techniques (especially for time series forecasting) and of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc.) is a huge plus.

·       Excellent presentation, written, and verbal communication skills for coordinating across teams.

·       Be able to work independently and as part of a team with 24/7 Support Operations.