RDSolutions - Machine Learning Engineer - Python

Job Description

Description : Title : ML Type : Full time, : : BE/B.tech/MCA Degree in Computer Science, Engineering, or similar relevant Experience : 4+ Model : Work from the Role : We are seeking a skilled Machine Learning Engineer to design, build, and deploy scalable, data-driven solutions for enterprise environments. Responsibilities The ideal candidate will collaborate closely with clients and cross-functional teams to develop ML systems, optimize performance, and deliver measurable business Responsibilities : Collaborate with clients, data scientists, and engineering teams to deliver end-to-end machine learning solutions. Identify opportunities to implement new ML techniques and build pipelines to enable enterprise-scale deployment. Translate client requirements into data-driven models, processes, and analytical metrics. Analyze and transform large datasets across cloud platforms such as AWS, Azure, and GCP. Design, develop, and deploy advanced analytics solutions (e.g., recommender systems, NLP models, risk scoring). Productionize ML systems with a strong focus on optimization, scalability, and reliability. Contribute to practice growth through client presentations, proposal writing, business development activities, and mentoring junior team : Bachelors degree or equivalent experience. Hands-on experience handling and analyzing large (multi-billion-record) datasets. Strong programming skills in Python, Scala, or similar languages. Proficiency in SQL, MapReduce/Hive, NoSQL, and modern distributed data-processing frameworks. Working knowledge of data warehousing tools/environments such as Snowflake, Teradata, SQL Server, RDS, and Presto. Ability to frame data-driven business problems across industries. Experience in analytical domains such as consumer, marketing, financial, website, healthcare, or social media analytics. Hands-on expertise in implementing production-scale ML systems (NLP, personalization, computer vision, etc.) Understanding of DevOps and automation practices. Strong knowledge of statistics, modeling techniques, and model management/versioning. (ref:hirist.tech)