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2 Weeks ago
Direction Software LLP - Artificial Intelligence/Machine Learning Engineer - LLM Models
Gurugram, Haryana, India
Information Technology
Full-Time
Direction Software LLP
Overview
Position Overview
We are seeking a talented and motivated AI/ML Developers to join our team. As an AI/ML Developer, you will be responsible for developing and implementing AI/ML solutions, utilizing your expertise in AI/ML algorithms, programming languages (particularly Python), time-series analysis, forecasting, and cloud technologies. The ideal candidate will have experience working with AI/ML technologies and a strong foundation in software development principles.
Responsibilities
We are seeking a talented and motivated AI/ML Developers to join our team. As an AI/ML Developer, you will be responsible for developing and implementing AI/ML solutions, utilizing your expertise in AI/ML algorithms, programming languages (particularly Python), time-series analysis, forecasting, and cloud technologies. The ideal candidate will have experience working with AI/ML technologies and a strong foundation in software development principles.
Responsibilities
- Collaborate with cross-functional teams to identify and understand business requirements, and translate them into AI/ML solutions.
- Design, develop, and implement AI/ML algorithms and models, utilizing programming languages such as Python.
- Build and train machine learning models, utilizing frameworks such as TensorFlow, Keras, or PyTorch.
- Analyze large datasets, perform data pre-processing, including time-series data, and conduct feature engineering to improve model performance.
- Apply time-series analysis techniques for data exploration, trend identification, and anomaly detection.
- Develop forecasting models for predictive analytics and decision-making.
- Build solutions using modern Gen AI LLM frameworks.
- Optimize and fine-tune models to enhance accuracy, efficiency, and scalability.
- Utilize version control systems, particularly Git, to manage and track code changes and collaborate with team members effectively.
- Deploy AI/ML models on cloud platforms such as AWS, Azure, or Google Cloud, ensuring scalability and reliability.
- Monitor and maintain deployed models, conduct regular performance evaluations, and implement necessary updates and improvements.
- Stay up-to-date with the latest advancements in AI/ML technologies, frameworks, time-series analysis, and forecasting, and proactively suggest innovative solutions.
- Communicate and present technical concepts, findings, and recommendations to both technical and non-technical stakeholders.
- Professional experience working on AI/ML solutions, including hands-on experience with machine learning algorithms, deep learning frameworks, data pre-processing techniques, time-series analysis, and forecasting.
- Experience in building solutions using LLM tools and frameworks.
- Proficiency in programming languages, with a strong emphasis on Python, and familiarity with libraries and frameworks such as scikit-learn, pandas, NumPy, and SciPy.
- Experience using an experiment-tracking tool like mlflow.
- Strong understanding of statistical analysis, linear algebra, probability theory, and time-series concepts.
- Excellent knowledge of version control systems, particularly Git, and collaborative development workflows.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud, and experience with deploying and managing AI/ML models in a cloud environment.
- Solid understanding of software development principles and best practices, including testing, code documentation, and debugging.
- Excellent problem-solving and analytical skills, with the ability to work on complex AI/ML challenges and deliver high-quality solutions within deadlines.
- Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and present technical concepts to non-technical stakeholders.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field is desirable but not mandatory.
- Experience with big data processing frameworks such as Apache Hadoop, Spark, or Kafka.
- Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
- Knowledge of distributed computing and parallel processing concepts.
- Understanding of natural language processing (NLP) techniques and frameworks.
- Contributions to open-source AI/ML projects or research papers in the field.
- Relevant certifications in AI/ML technologies.
- Experience on data labelling tools, frameworks, and strategies
- Experience with ML/DL topologies like GraphML, GANs etc.
- Experience developing and deploying AI/ML solutions using DS/ML platforms
- Understanding of REST services and microservices architecture
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