We Love AI JobsMachine Learning Engineer
GalentJoin Galent as a Machine Learning Engineer and work on cutting-edge AI applications while collaborating with skilled data engineers. With a focus on building and deploying machine learning models and data pipelines, this full-time role offers the chance to impact various industries, including Oil & Gas and Retail, through advanced analytics solutions.
Skills & Expertise
Key Responsibilities
Develop and deploy machine learning models for various applications.
Collaborate with data teams to operationalize ML models effectively.
Translate business problems into analytical solutions with clear insights.
Full Description
Key Responsibilities
* Develop and deploy machine learning models for prediction, forecasting, segmentation, and optimization
* Build AI-powered applications using LLMs, embeddings, and Retrieval-Augmented Generation (RAG) pipelines
* Design and implement scalable data pipelines for large and complex datasets
* Develop APIs and data-driven applications to operationalize ML models
* Collaborate with data engineering teams to deploy and monitor models in production environments
* Build lightweight dashboards or user interfaces (e.g., Streamlit, Dash) for business users
* Translate business problems into analytical solutions and communicate insights effectively
* Ensure adherence to best practices in data governance, security, and privacy
Required Skills & Qualifications
* 4+ years of experience in Data Science, Machine Learning, or AI-related roles
* Strong programming skills in Python (Pandas, NumPy, Scikit-learn) and SQL
* Hands-on experience with machine learning techniques (classification, regression, clustering, forecasting)
* Experience working with large datasets and performing advanced feature engineering
* Strong analytical and problem-solving skills
* Excellent communication and collaboration abilities
Preferred Qualifications
* Experience with Generative AI frameworks (OpenAI, LangChain, Hugging Face, RAG architectures)
* Familiarity with cloud platforms such as AWS, Azure, Databricks, or Snowflake
* Experience with distributed data processing frameworks like Spark
* Exposure to front-end tools such as Streamlit, Dash, or React
* Experience deploying ML models via APIs or building end-to-end AI applications
* Domain experience in Oil & Gas, Energy, Retail, or Marketing analytics