3 Recommendation System Jobs

The next step of your career starts here, where you can bring your own unique mix of skills and perspectives to a fast-growing team. Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities. With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself. We are Metyis. Partners for Impact. Interact with C-level at our clients on a regular basis to drive their business towards impactful change. Lead your team in creating new business solutions. Seize opportunities at the client and at Metyis in our entrepreneurial environment. Become part of a fast-growing international and diverse team. Lead and manage the delivery of complex data science projects, ensuring quality and timelines. Engage with clients and business stakeholders to understand business challenges and translate them into analytical solutions. Design solution architectures and guide the technical approach across projects. Align technical deliverables with business goals, ensuring data products create measurable business value. Communicate insights clearly through presentations, visualizations, and storytelling for both technical and non-technical audiences. Promote best practices in coding, model validation, documentation, and reproducibility across the data science lifecycle. Collaborate with cross-functional teams to ensure smooth integration and deployment of solutions. Drive experimentation and innovation in AI/ML techniques, including newer fields - Generative AI. 6+ years of experience in delivering full-lifecycle data science projects. Proven ability to lead cross-functional teams and manage client interactions independently. Strong business understanding with the ability to connect data science outputs to strategic business outcomes. Experience with stakeholder management, translating business questions into data science solutions. Track record of mentoring junior team members and creating a collaborative learning environment. Familiarity with data productization and ML systems in production, including pipelines, monitoring, and scalability. Experience managing project roadmaps, resourcing, and client communication. Strong hands-on experience in Python/R and SQL. Good understanding and Experience with cloud platforms such as Azure, AWS, or GCP. Experience with data visualization tools in python like Seaborn, Plotly. Good understanding of Git concepts. Good experience with data manipulation tools in python like Pandas and Numpy. Must have worked with scikit learn, NLTK, Spacy, transformers. Experience with dashboarding tools such as Power BI and Tableau to create interactive and insightful visualizations. Proficient in using deployment and containerization tools like Docker and Kubernetes for building and managing scalable applications. Core Competencies: Strong foundation in machine learning algorithms, predictive modeling, and statistical analysis. Good understanding of deep learning concepts, especially in NLP and Computer Vision applications. Proficiency in time-series forecasting and business analytics for functions like marketing, sales, operations, and CRM. Exposure to tools like Mlflow, model deployment, API integration, and CI/CD pipelines. Hands-on experience with MLOps and model governance best practices in production environments. Experience in developing optimization and recommendation system solutions to enhance decision-making, user personalization, and operational efficiency across business functions. Generative AI Experience with text and Image data. Familiarity with LLM frameworks such as LangChain and hubs like Hugging Face. Exposure to vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search or retrieval-augmented generation (RAG).,

The Machine Learning Engineer role focuses on enhancing interactions across user gaming experiences and systems by designing, coding, training, documenting, deploying, and evaluating large-scale machine learning systems efficiently. You will have the opportunity to create exceptional products and experiences for millions of users within an agile environment, collaborating seamlessly with other teams. Immersion in cutting-edge ML technologies, tools, and processes is a key aspect, contributing to the advancement of technical objectives and architectural initiatives. As an ML Engineer, your responsibilities include designing and developing machine learning models and algorithms tailored to various applications. Implementation and optimization of these models are crucial tasks, alongside collaborating with cross-functional teams to integrate the models into production systems effectively. Staying updated with the latest advancements in machine learning and AI technologies is essential to ensure solutions remain cutting-edge and effective. Your tasks will involve: - Developing, implementing, and optimizing machine learning models for applications such as predictive safety, content personalization, search, virtual assistant, time series forecasting, and clustering. - Utilizing state-of-the-art machine learning and deep learning technologies for multilingual text classification, language modeling, and multi-modal learning. - Collaborating with cross-functional teams to understand business requirements and translate them into analytical solutions. - Conducting thorough exploratory data analysis to uncover patterns, trends, and valuable insights. - Deploying machine learning models into production environments using AWS services and implementing scalable solutions for real-time and batch predictions. Required Skills and Qualifications: - Bachelor's degree in computer science, Engineering, Statistics, or a related field. - 5+ years of working experience in advanced machine learning areas like computer graphics, reinforcement learning, recommendation systems, and natural language processing. - Proficiency in Python programming and experience with PyTorch, TensorFlow, or similar frameworks. - Experience in designing and implementing machine learning-based solutions, including online safety, conversational systems, recommender systems, search engines, personalization, time series forecasting, and A/B testing. - Strong machine learning, statistical, and analytical skills. What We Offer: - Bootstrapped and financially stable with high pre-money evaluation. - Above industry remunerations. - Additional compensation tied to Renewal and Pilot Project Execution. - Additional lucrative business development compensation. - Opportunity to work closely with industry experts driving strategy with data and analytics. - Firm building opportunities for holistic professional development, growth, and branding. - Empathetic, excellence, and result-driven organization that believes in mentoring and growing a team with a constant emphasis on learning.,

We are seeking a highly skilled and motivated Lead Data Scientist to join our team. In this role, you will leverage cutting-edge AI and machine learning technologies to solve complex business problems, design innovative data science solutions, and deliver projects that exceed client expectations. As a leader, you will manage a team of data scientists, collaborate with cross-functional data teams, and provide strategic and technical direction in data science while driving innovation in our product and solution offerings. Mandatory Technical Skills: • Strong statistical and machine learning intuition to address new and unique challenges. • Ability to design, develop and deploy end-to-end data science solutions, POCs and production-grade applications. • Strong proficiency in Python with OOP principles - ( 4 years of experience) • Experience developing APIs using Flask or Fast API frameworks ( 2 years of experience) • Integration knowledge with front-end applications ( 1 year of experience) • Expertise in version control systems (e.g., GitHub, GitLab, Azure DevOps) - ( 3 years of experience) • Familiarity with task management tools (e.g., Jira, Azure DevOps) - ( 2 years of experience) • Proficiency in databases, including SQL, NoSQL and vector databases ( 2 + years of experience) • Working knowledge of ML pipelines and CI/CD. • Experience with at least one of the cloud platforms (Azure, AWS, GCP) - ( 2 + years of experience) Core Excellence Areas (CEA): Candidates must have a strong understanding of fundamentals and good hands-on expertise in at least THREE of the following areas (mention your areas while applying): NLP Generative AI (NLP) Computer Vision Time Series Forecasting Recommendation Systems and Optimization Roles & Responsibilities: • Advanced AI/ML/Gen AI Implementation: o Leverage advanced AI and machine learning techniques to address complex business challenges. o Design, develop, and deliver innovative data science solutions. • Architectural Design: o Develop end-to-end generative AI solutions. o Build scalable architectures for AI/ML models and applications. • Team Leadership: o Lead and mentor a team of data scientists, fostering professional growth and technical excellence. o Provide strategic and technical guidance to ensure the team delivers high-quality projects. • Cross-functional Collaboration: o Work closely with data engineering, product, and business teams to align on objectives and integrate solutions. • Client Engagement : Maintain high levels of client satisfaction through excellent communication, delivering impactful solutions, and building strong relationships. • Innovation: Ideate and implement new approaches for products and solutions, ensuring they stay at the forefront of technology. Nice to have Skills: • Hands-on experience with PySpark, large-scale data processing using distributed frameworks and parallel processing. • Hands-on experience with Azure AI stack, ETL processes, and integration with analytics tools (e.g., Power BI, Tableau) • Knowledge of deep learning frameworks (e.g., PyTorch, TensorFlow, Keras). • Experience with cloud platforms and MLOps practices. • Project management skills to lead initiatives effectively. • Knowledge of graph-based query languages (e.g., Cypher, Gremlin) and Proficiency in graph databases. Experience & Educational Qualifications: • Minimum of 5+ years of experience solving complex machine learning problems. • At least 2+ years of hands-on experience in each of the chosen Core Excellence Areas. • Minimum of 1 year leading and managing ML projects end-to-end. • Bachelors degree in computer science, Data Science, or related field (Master’s/PG AI/ML/DS preferred).