Software Engineer
1 month ago
The Company
Datamtx (www.datamtx.com / formerly Datamatics) established in 1993 and globally HQ‘d in Atlanta has a stellar history supporting both Tier 1 and 2 ERP rollouts ranging from implementations, data cleanse, migrations, customization, hypercare and Day 1 support. We are also nationally aligned with leading accounting firms & VARs.
Our ERP coverage includes: SAP, Oracle EBS/Fusion, Peoplesoft, JDE, Infor (M3, LX, XA, LN, System 21), IFS, Epicor, SysPro, D365.
One of our longest standing service verticals has been assisting transition clients from legacy systems to cloud based platforms including introduction of AGI / GenAI and Computer Vision models.
We are seeking a Software Engineer with Artificial Intelligence, Machine Learning and Python experience.
This will will be a 100% remote job.
Interview Process: 3 interviews.
1st Interview: Video call with Hiring Manager call | 2nd Interview: Video call with Team members | 3rd Interview: Meeting with Sr. Team Manager
Hiring Manager Notes:
The AI-ML team is a newer team within this client and they are small but growing rapidly. We currently are building our team and need experienced individuals that can experience to join our team and hit the ground running. We do not have an existing AI-ML team located offshore. So, this resource will need to work efficiently and professionally with little direct supervision.
Job Summary:
We are seeking a talented Software Engineer with expertise in machine learning to join our newly formed Artificial Intelligence (AI) and Machine Learning (ML) team. As a Software Engineer, you will play an important role in supporting the AI and ML Computer Vision lead in training ML models and help them create training datasets, label and annotate these data sets for ongoing training, feedback and inference. There will be ample opportunities to create computer vision models touching some of the client‘s most vital processes.
Primary Job Duties:
1. Collaborate with cross-functional teams to understand business requirements and identify opportunities for machine learning techniques.
2. Analyze and evaluate existing systems and processes to identify areas where machine learning can be leveraged to improve efficiency, accuracy, and decision-making.
3. Work with engineering-leads to design and develop machine learning models and algorithms to solve complex business problems, such as recommendation systems and computer vision models.
4. Collect, clean, and preprocess (label and annotate) data from various sources to train machine learning models.
5. Train, validate, and fine-tune machine learning models using appropriate algorithms and techniques.
6. Collaborate with data engineers and software developers to integrate machine learning models into existing systems and new applications.
7. Conduct thorough testing and validation of machine learning solutions to ensure their accuracy, reliability, and scalability.
8. Monitor and evaluate the performance of deployed machine learning models, making necessary adjustments and improvements as needed.
Required Qualifications:
1. bachelor’s degree in computer science, AI&ML, Data Science, or a related field.
2. Proven experience in creating training data sets, labeling, and annotating data sets for Machine Learning projects.
3. Strong understanding of machine learning algorithms, techniques, and frameworks.
4. Proficiency in Python or similar programming language needed for Machine Learning.
5. Experience with machine learning libraries and frameworks, like TensorFlow or PyTorch..
6. Solid knowledge of data preprocessing, feature engineering, and model evaluation techniques.
7. Familiarity with any of cloud platforms like AWS or GCP, and experience deploying and managing models.
8. Strong analytical and problem-solving skills, with the ability to think critically and creatively to solve complex business problems.
9. Excellent communication and collaboration skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
Preferred Qualifications:
1. Master‘s degree or higher in Computer Science, Data Science, or a related field.
2. Experience working on AI and ML projects in a professional setting.
3. Familiarity with data visualization tools and techniques for communicating machine learning results
4. Experience with natural language processing (NLP) and computer vision techniques.
5. Understanding of software development methodologies, such as Agile or DevOps.
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