ML Engineer

About Saarthee:

Saarthee is a Global Strategy, Analytics, Technology and AI consulting company, where our passion for helping others fuels our approach and our products and solutions. Our diverse and global team work with one objective in mind: Our Customers’ Success. At Saarthee, we are passionate about guiding organizations to wards insights fueled success. That’s why we call ourselves Saarthee-inspired by the Sanskrit word ‘Saarthi’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with office in UK and India.

About the Role:

We are looking for a Machine Learning Engineer (4-7 years) with strong fundamentals in Machine Learning and Deep Learning. The candidate should have hands-on experience with model development using Python and ML frameworks, along with exposure to Generative AI and Agentic AI concepts. Good problem-solving skills and the ability to work in a collaborative environment are essential.

Responsibilities:

• Design, develop, and deploy Machine Learning solutions for Online User Safety use cases of a gaming product.
• Build and optimize ML/DL models for classification and prediction problems.
• Work with cross-functional teams to understand business requirements and deliver AI solutions.
• Perform data preprocessing, feature engineering, model training, and evaluation.
• Develop and maintain scalable ML pipelines.
• Contribute to GenAI and Agentic AI based solutions where applicable.
• Monitor model performance and continuously improve accuracy.
• Follow software engineering best practices, code reviews, and documentation.

Qualifications:

• Graduation or master's in computer science & Engineer or related field. 7+ Years of IT experience ;3+ Years of AI/ML
• 3+ years of working experience in at least one of the advanced machine learning areas including Linear Regression, Logistic Regression, Classification, feature engineering, model evaluation ( Accuracy, Precision, Recall), artificial neural network
• Expertise in the Python programming language.
• Experience in designing and implementing machine learning-based solutions that ideally include online safety, voice-activated conversational systems, recommender systems, search engines, personalization, time series forecasting, and A/B testing.
• Strong machine learning, statistical and analytical skills.

Required Skills: Linear Regression, Logistic Regression, Classification, Feature Engineering, Model Evaluation (Accuracy, Precision, Recall), Artificial Neural Networks (ANN), Python, Statistics, SQL, Retrieval-Augmented Generation (RAG), Agentic AI.

Skills to Evaluate: Overfitting & Regularization, Artificial Neural Networks (ANN), Linear Regression, Logistic Regression, Classification, Feature Engineering, Model Evaluation (Accuracy, Precision, Recall), Python, Statistics, SQL, Retrieval-Augmented Generation (RAG), and Agentic AI.