BD&I ML Engineer IRC276081

Description

Must have skills:

Python azure data factory Databricks Apache Spark / PySpark Azure Data Lake Store Azure Data Lake Analytics Pipeline Execution/ETL Machine Learning AI ETL clould data pipelines Docker Kubernetes AWS

Requirements

About the Role
We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities
Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.
Conduct exploratory data analysis and feature engineering to improve model performance.
Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.
Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.
Monitor and optimize the performance of deployed models in production.
Stay up-to-date with the latest advancements in machine learning and related technologies.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems
Communicate technical concepts and findings to both technical and non-technical audiences.
Stay abreast of the latest advancements in data science and machine learning techniques.
Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:
2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.
Excellent problem-solving and analytical skills.
Communication and collaboration skills.
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
3+ years of experience in developing and deploying machine learning models in a professional setting.
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.

Soft Skills:
Strong problem-solving and critical thinking skills
Ability to break down complex technical topics for business stakeholders
Comfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:
Bachelor’s degree in Computer Science or related field.
Master’s degree or equivalent advanced degree preferred.
Proven track record of delivering data science projects from ideation to production.
Strong communication skills and the ability to tell compelling stories with data.
Comfortable with both structured and unstructured data sets.

Job responsibilities

About the Role
We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities
Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.
Conduct exploratory data analysis and feature engineering to improve model performance.
Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.
Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.
Monitor and optimize the performance of deployed models in production.
Stay up-to-date with the latest advancements in machine learning and related technologies.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems
Communicate technical concepts and findings to both technical and non-technical audiences.
Stay abreast of the latest advancements in data science and machine learning techniques.
Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:
2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.
Excellent problem-solving and analytical skills.
Communication and collaboration skills.
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
3+ years of experience in developing and deploying machine learning models in a professional setting.
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.

Soft Skills:
Strong problem-solving and critical thinking skills
Ability to break down complex technical topics for business stakeholders
Comfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:
Bachelor’s degree in Computer Science or related field.
Master’s degree or equivalent advanced degree preferred.
Proven track record of delivering data science projects from ideation to production.
Strong communication skills and the ability to tell compelling stories with data.
Comfortable with both structured and unstructured data sets.

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.