Infor is seeking a Software Engineer who is passionate about developing high-quality, scalable software solutions with application of Data Science/ML/AI/GenAI. You will work closely with researchers, senior engineers, product managers, and designers to deliver products that drive business value for our customers. This role is ideal for early-to-mid-career engineers who thrive in collaborative, agile environments and are eager to grow technical and leadership skills.
Position Summary:
You will team with other development partners and drive foundational AI research into different products like Digital Assistant and Document Capture.
You will work with all component partners to implement the vision and roadmap leveraging DS, AI and ML in different products.
Essential Duties:
As an AI and ML engineer specializing in technologies like image processing, personal assistant, risk assessment, etc., your essential duties would involve a combination of research, development, and implementation tasks.
Here are some key responsibilities you can expect in this role:
Continuously evaluate and enhance the performance and capabilities of the deployed AI products. Keep track of user feedback and re-train & iterate on the models and algorithms to address limitations and improve user experience.
Collaborate with cross-functional teams, including researchers, engineers, designers, and product managers, to define requirements, align objectives, and deliver high-quality solutions. Effectively communicate research findings, technical concepts, and project progress.
Basic Qualifications & Skills:
To be an AI and ML expert, you would require a combination of educational qualifications, technical skills, and personal attributes. Here are some qualifications that would be beneficial for such a role:
Educational Background:
· Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics or a related field.
Optionally, a specialization or coursework in AI, ML, Statistics & Probability, DL, Computer Vision, Signal Processing, or NLP/NLU is a plus.
Foundation in AI and ML:
3-6 years of experience in analyzing data and implementing AI/ML models.
Working in Big Data platforms for business problems is a plus.
Require good understanding of at least a couple of AI/ML algorithms. This may include supervised and unsupervised learning, reinforcement learning, deep learning, probabilistic models, generative AI models, etc.
Programming and Tools:
· Proficiency in programming languages commonly used in AI and ML is essential, such as Python & querying languages like SQL.
Experience with relevant python libraries and frameworks is a plus.
Ability to work with large datasets, data preprocessing, and data wrangling.
Preferred Skills:
Problem-Solving and Analytical Skills:
Strong analytical and critical thinking abilities to identify and define problems, formulate hypotheses, and design experiments.
Capacity to break down complex problems into manageable tasks and propose effective solutions.
Attention to detail and ability to analyze and interpret data accurately.
Communication and Collaboration:
Excellent written and verbal communication skills to articulate complex technical concepts to both technical and non-technical stakeholders.
Collaborative mindset and ability to work effectively in interdisciplinary teams.
Strong presentation skills to deliver research findings and project updates.
Continuous Learning:
Eagerness to stay updated with the latest advancements in AI and ML through self-study, research papers, conferences, or workshops.
Willingness to adapt to new technologies, tools, and methodologies.
Position Summary:
You will team with other development partners and drive foundational AI research into different products like Digital Assistant and Document Capture.
You will work with all component partners to implement the vision and roadmap leveraging DS, AI and ML in different products.
Essential Duties:
As an AI and ML engineer specializing in technologies like image processing, personal assistant, risk assessment, etc., your essential duties would involve a combination of research, development, and implementation tasks.
Here are some key responsibilities you can expect in this role:
Continuously evaluate and enhance the performance and capabilities of the deployed AI products. Keep track of user feedback and re-train & iterate on the models and algorithms to address limitations and improve user experience.
Collaborate with cross-functional teams, including researchers, engineers, designers, and product managers, to define requirements, align objectives, and deliver high-quality solutions. Effectively communicate research findings, technical concepts, and project progress.
Basic Qualifications & Skills:
To be an AI and ML expert, you would require a combination of educational qualifications, technical skills, and personal attributes. Here are some qualifications that would be beneficial for such a role:
Educational Background:
· Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics or a related field.
Optionally, a specialization or coursework in AI, ML, Statistics & Probability, DL, Computer Vision, Signal Processing, or NLP/NLU is a plus.
Foundation in AI and ML:
3-6 years of experience in analyzing data and implementing AI/ML models.
Working in Big Data platforms for business problems is a plus.
Require good understanding of at least a couple of AI/ML algorithms. This may include supervised and unsupervised learning, reinforcement learning, deep learning, probabilistic models, generative AI models, etc.
Programming and Tools:
· Proficiency in programming languages commonly used in AI and ML is essential, such as Python & querying languages like SQL.
Experience with relevant python libraries and frameworks is a plus.
Ability to work with large datasets, data preprocessing, and data wrangling.
Preferred Skills:
Problem-Solving and Analytical Skills:
Strong analytical and critical thinking abilities to identify and define problems, formulate hypotheses, and design experiments.
Capacity to break down complex problems into manageable tasks and propose effective solutions.
Attention to detail and ability to analyze and interpret data accurately.
Communication and Collaboration:
Excellent written and verbal communication skills to articulate complex technical concepts to both technical and non-technical stakeholders.
Collaborative mindset and ability to work effectively in interdisciplinary teams.
Strong presentation skills to deliver research findings and project updates.
Continuous Learning:
Eagerness to stay updated with the latest advancements in AI and ML through self-study, research papers, conferences, or workshops.
Willingness to adapt to new technologies, tools, and methodologies.