Bachelor's or Master's degree in a relevant field such as Computer Science, Data Science, or Mathematics.
3-7 years of experience in Machine Learning or AI roles.
Hands-on experience with deploying machine learning models in production environments.
Familiarity with Agile development methodologies.
Experience working with large-scale datasets and distributed computing frameworks.
Responsibilities
Design, develop, train, and deploy machine learning models and algorithms.
Build scalable data pipelines for data collection and processing.
Evaluate and optimize machine learning models for accuracy and performance.
Collaborate with teams to translate business requirements into machine learning solutions.
Deploy and monitor models in production environments.
Perform model validation and performance tuning.
Develop and maintain MLOps workflows for continuous deployment.
Benefits
Flexible work environment with remote, hybrid, or on-site options.
Opportunity to work on cutting-edge AI projects.
Access to continuous learning and professional development.
Collaborative and innovative team culture.
Exposure to emerging machine learning technologies and practices.
Full Job Description
Job Title:
Machine Learning Engineer
Job Summary:
We are seeking a talented and innovative Machine Learning Engineer to design, develop, deploy, and maintain machine learning models and AI-powered solutions. The ideal candidate will work closely with data scientists, software engineers, and business stakeholders to build scalable machine learning systems that solve complex business problems and drive data-driven decision-making.
Key Responsibilities:
Design, develop, train, and deploy machine learning models and algorithms.
Build scalable data pipelines for data collection, processing, and feature engineering.
Evaluate and optimize machine learning models for accuracy, performance, and scalability.
Collaborate with cross-functional teams to understand business requirements and translate them into AI/ML solutions.
Deploy and monitor machine learning models in production environments.
Perform model validation, testing, and performance tuning.
Develop and maintain MLOps workflows for continuous integration and deployment of ML models.
Analyze large datasets to identify trends, patterns, and opportunities for predictive analytics.
Research and implement emerging AI and machine learning technologies.
Document model architectures, processes, and technical solutions.
Required Skills:
Strong understanding of Machine Learning, Deep Learning, and Artificial Intelligence concepts.
Experience with supervised and unsupervised learning algorithms.
Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Strong analytical and problem-solving abilities.
Experience deploying machine learning solutions into production.
Excellent communication and collaboration skills.
Technical Skills:
Programming Languages: Python, R, Java
Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch, Keras
Data Processing: Pandas, NumPy, Apache Spark
Databases: MySQL, PostgreSQL, MongoDB
Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP)
MLOps Tools: MLflow, Kubeflow, Airflow
Version Control: Git, GitHub, GitLab
Containerization: Docker, Kubernetes
Data Visualization: Matplotlib, Seaborn, Power BI, Tableau
Qualifications:
Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
Relevant AI/ML certifications are a plus.
Experience:
3-7 years of experience in Machine Learning, Data Science, or AI-related roles.
Hands-on experience building and deploying machine learning models in production environments.
Experience working with large-scale datasets and distributed computing frameworks.
Familiarity with Agile development methodologies.
Preferred Qualifications:
Experience with Generative AI, Large Language Models (LLMs), and Natural Language Processing (NLP).
Knowledge of Computer Vision and Deep Learning frameworks.
Experience with Retrieval-Augmented Generation (RAG) architectures.
Familiarity with vector databases such as Pinecone, Weaviate, or ChromaDB.
Experience integrating AI services through APIs and cloud-based AI platforms.
Preferred Qualities:
Strong problem-solving and critical-thinking skills.
Passion for innovation and emerging AI technologies.
Ability to work independently and in a collaborative environment.
Excellent communication and presentation skills.
Commitment to continuous learning and professional development.
Employment Type:
Full-Time
Location:
Remote / Hybrid / On-site (based on company requirements)
Nice to Have:
Experience with Generative AI tools such as OpenAI APIs, Claude, Gemini, or similar platforms.
Knowledge of LLM fine-tuning, prompt engineering, and AI model evaluation.
Experience building AI-powered chatbots, recommendation engines, or predictive analytics solutions.
Contributions to open-source AI/ML projects or published research in machine learning.
