Machine Learning Jobs - Apr-May 2024

Job description:

• As a Machine Learning Engineer, you will collaborate on real-world projects, assist in data analysis, and contribute to the development of machine learning models.

Role Responsibilities:

• Data Analysis: Assist in collecting, cleaning, and analyzing large datasets to derive meaningful insights for machine learning models.
• Model Development: Collaborate with the machine learning team to develop and implement algorithms and models that align with project goals.
• Code Development: Contribute to the coding and programming tasks required for the implementation and optimization of machine learning algorithms.
• Research: Stay current on the latest trends, techniques, and advancements in machine learning and artificial intelligence.
• Testing and Evaluation:Conduct experiments, tests, and evaluations to ensure the effectiveness and accuracy of machine learning models.
• Documentation: Prepare comprehensive documentation for the developed models, algorithms, and methodologies.
• Collaboration: Work closely with cross-functional teams, including software developers and domain experts, to integrate machine learning solutions into real-world applications.
• Problem Solving: Identify and address challenges related to data quality, model performance, and scalability.

Qualifications:

• Currently pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field.
• Strong programming skills in languages such as Python or R.
• Familiarity with machine learning frameworks (TensorFlow, PyTorch, etc).
• Solid understanding of data structures, algorithms, and statistical concepts.
• Excellent analytical and problem-solving abilities.
• Effective communication skills and ability to work collaboratively in a team.

Job description:

• Advanced mathematical and statistical skills in subjects like linear algebra, calculus, and Bayesian statistics.
• Degree in computer science, mathematics, statistics, or a related field.
• Professional knowledge in machine learning, neural networks, deep learning, or related fields.
• Analytical, problem-solving, and team player.
• Software engineering skills.
• Knowledge in data science.
• Coding and programming languages: Python, Java, C++, C, R, and JavaScript.
• Understand ML frameworks, libraries and packages, data structures, data modeling, and software architecture.

Overall Responsibilities:

• Designing ML systems.
• Design and create AI algorithms capable of learning and making predictions.
• Researching and implementing ML algorithms and tools.
• Identifying appropriate data sets, data representation methods, differences in data distribution, and verifying data quality.
• Transforming and converting data science prototypes.
• Performing statistical analysis.
• Running machine learning tests and using results to improve models.
• Training and retraining systems when needed.
• Extending machine learning libraries.
• Developing machine learning apps according to client requirements.

Responsibilities

• Conducts advanced analytics leveraging predictive modeling, machine learning, simulation, optimization, and other techniques to intelligent features for Calix Cloud services.
• Develop scalable, efficient, automated systems for large scale data analyses, model development, model validation and model implementation.
• Develop efficient data processing and feature engineering pipelines at production scale
• Integrate with upstream and downstream applications, data sources
• Select, implement, test and optimize models at training and inferencing time
• Work with scientist and product team to define, collect and monitor data/model metrics
• Monitor and maintain deployed models and pipelines in production
• Develop and extend ML frameworks to enhance ML development processes
• Collaborate with scientist and Ops to develop, deploy, monitor, and optimize ML pipelines
• Support ML pipeline in production and debug into issues
• Optimize ML pipelines and algorithms for better scalability, SLA and stability

Qualifications:

• 5+ years of solid experience in production software engineering roles
• 3+ years focused on data and ML engineering
• Solid foundation on data structure and algorithms.
• Proficiency in some of these languages: Python, Java, Scala, R, C/C++, SQL
• Solid experience working with ML frameworks like: scikit-learn, TensorFlow, Keras, PyTorch.
• Passionate in solving complex data problems, optimize ML algorithms to meet or exceed SLA.
• Experience in troubleshooting production issues on ML models and pipelines.
• Experience in building production, end-to-end scalable ML pipelines.
• Experience in processing large datasets with SQL/NoSQL options like Spark, Presto, S3.
• Experience using feature store to support multiple use cases.
• Clear understanding of data processing and storage challenges on distributed architecture.
• Prior experience shipping scalable data solutions in the cloud (AWS, Azure, GCP) and database technologies such as Snowflake, Redshift, SQL/NoSQL and or columnar databases.
• Good communication skills.
• BS degree in a related field.

Preferred Qualifications:

• Good exposure to statistical learning and computational linear algebra.
• Experience productizing machine learning pipelines on Kubernetes based platform.
• Experience with use cases in digital marketing, predictive maintenance and NLP techniques.

Responsibilities

• Develops and reviews complex data analytics models, algorithms, systems and solutions, using advanced and specialist data science, programming and analytical techniques
• Delivers complex predictive models and identifies new projects, opportunities and data sources which can be used to drive measurable client and commercial benefit
• Provides insights and recommendations from different data sources to senior team members to help make decisions that drive better business outcomes for clients
• Working closely with senior team members to scope, identify and establish appropriate data analysis methodologies for projects Seeking new data sources internally and externally that enable leading edge data science solutions
• Developing complex statistical modelling tools that drive business outcomes for clients, involving complex algorithms, artificial intelligence methods, machine learning, deep learning and advanced statistics

Skills Required

Python - Machine Learning and Deep Learning - Natural Language Processing - TensorFlow, PyTorch

Job Description

You will collaborate with software engineers and product managers to create effective artificial intelligence algorithms, where “effective” means that specific outputs can be traced back to particular inputs. As an AI machine learning engineer, we hope you can put your passion for AI engineering toward creating a safe and effective AI partner. We are especially looking for Lead - Machine Learning with a strong background in Analytics, Data mining, Machine Learning, Pattern Recognition and Natural Language Processing.

Machine Learning Engineer will report to Director Engineering - Machine Learning & the roles & responsibilities are as below:

• Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Managing available resources such as hardware, data, and personnel so that deadlines are met
• Analysing the ML/NLP algorithms that could be used to solve a given problem and ranking them by their success probability
• Exploring and visualising data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Supervising the data acquisition process if more data is needed
• Finding available datasets online that could be used for training
• Defining validation strategies
• Defining the preprocessing or feature engineering to be done on a given dataset
• Defining data augmentation pipelines
• Training models and tuning their hyper-parameters
• Analysing the errors of the model and designing strategies to overcome them
• Deploying models to production
• Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems
• Clear communication with product managers and other engineers regarding project timelines, delays, advancements, and progression

Requirements

• Bachelor’s, Master’s or PhD degree in a related field, such as computer science, software engineering or data science, is recommended.
• Graduate/Post Graduate from Tier I institutes.
• Proficiency in PyTorch, Python, Java, or OpenAI is a plus
• Minimum 3-8 years of experience as a certified engineer
• Experience working with SaaS companies
• Comfort controlling the big data feed that will be used to train the AI
• Attention to detail and ability to respond quickly
• Strong analytical skills
• Must have prior experience of handling teams.
• 3-8 years of experience manipulating data sets and building statistical models
• Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience in visualizing/presenting data.