About the job

OptiComm.AI is an intelligent prediction platform that helps businesses accurately forecast customer needs and uncover hidden revenue opportunities. Our platform goes beyond traditional solutions that rely heavily on historical data and combines state-of-the-art deep learning forecasting with reality-based workflows, external market information, and contextual intelligence. OptiComm.AI predicts more than orders, it predicts customer needs.

We’re currently expanding our AI capabilities and working with major enterprise clients across retail, logistics, and supply chain industries.

Role Overview: As a Machine Learning Engineer at OptiComm.AI, you’ll lead the design and implementation of cutting-edge ML/DL models that power our intelligent prediction platform. You’ll work at the intersection of advanced forecasting, anomaly detection, and prescriptive analytics to create solutions that transform how businesses predict and proactively shape their future.

Key Responsibilities:

• Lead ML Model Development: Design, develop, and optimize advanced machine learning and deep learning models for demand forecasting, revenue generation, and cost optimization 
• Feature Engineering: Develop sophisticated feature engineering approaches that extract maximum value from complex, multi-dimensional datasets 
• Model Deployment & Scaling: Work with data and platform engineers to deploy models at scale in enterprise environments 
• Performance Optimization: Continuously improve model accuracy, efficiency, and business impact through rigorous testing and refinement 
• Multi-Modal Integration: Integrate external data sources (demographic, economic, seasonal, competitive) to enrich our prediction capabilities 
• Research & Innovation: Stay at the forefront of ML/AI advancements and implement new techniques that enhance our prediction platform 
• Team Leadership: Mentor junior ML engineers and provide technical direction on model development 
• Client Solutions: Collaborate with implementation teams to customize models for specific client needs across various industries

Requirements:

• Experience: 3+ years of professional experience in machine learning engineering roles 
• Education: Master’s or PhD in Computer Science, Machine Learning, AI, or related technical field 
• Technical Expertise: Proficiency in Python and machine learning frameworks (PyTorch, scikit-learn) 
• Model Development: Proven experience designing and implementing production-grade ML/DL models 
• Time Series Mastery: Deep expertise in time series forecasting, anomaly detection, and predictive modeling 
• Data Processing: Advanced skills in data preparation, feature engineering, and model evaluation 
• MLOps Knowledge: Experience with ML model deployment, monitoring, and lifecycle management 
• Business Understanding: Ability to translate business problems into effective ML solutions 

Nice to Have:

• Experience with retail, logistics, or supply chain forecasting models 
• Expertise in cloud ML services (Microsoft Fabric, Azure ML, AWS SageMaker, Google Vertex AI) 
• Knowledge of reinforcement learning or prescriptive analytics 
• Experience with large-scale data processing using distributed computing frameworks 
• Familiarity with modern ML infrastructure and containerization 
• Experience working with enterprise customers in B2B environments

What We Offer

• Opportunity to shape the future of AI-driven business intelligence
• Work with cutting-edge technology in partnership with major tech companies
• Collaborative environment with a team of experienced professionals
• Competitive compensation package
• Professional development and learning opportunities
• Flexible work arrangements

We believe in shared success—that’s why we offer equity in our rapidly growing venture, making you a true stakeholder in our journey toward revolutionizing demand prediction. “

Join us in revolutionizing how businesses predict and shape their future through intelligent, actionable insights!