Software Engineer – ML at Indix provides an opportunity to design and build systems that crunch large amounts of data everyday What We’re Looking For- 3+ years of experience Ability to propose hypothesis and design experiments in the context of specific problems. Should come from a strong engineering background Good overlap with Indix Data tech stack such as Hadoop, MapReduce, HDFS, Spark, Scalding, Scala/Python/C++ Dedication and diligence in understanding the application domain, collecting/cleaning data and conducting experiments. Creativity in model and algorithm development. An obsession to develop algorithms/models that directly impact business. Master’s/Phd. in Computer Science/Statistics is a plus Job Expectations Experience working in text mining and python libraries like scikit-learn, numpy, etc Collect relevant data from production systems/Use crawling and parsing infrastructure to put together data sets. Survey academic literature and identify potential approaches for exploration. Craft, conduct and analyze experiments to evaluate models/algorithms. Communicate findings and take algorithms/models to production with end to end ownership.
Job Description Responsibilities - Develop Machine Learning Models - Develop CNN models with Tensorflow - Develop UI using latest technologies Desired Skills - We use Python, Go, Tensorflow, Docker, and PostgreSQL, but frequently change technologies and learn new skills very quickly - Experience with SQL databases is a plus - Passionate about clean, well-documented code with unit tests - Knowledge of functional programming is a plus Desired Personal Qualities - Proactive. - Future optimistic. - Positive. - Correct. - Passionate. - Insane. Contrarian. - Honest. Trustworthy.
We are looking for Freelance online Data Scientist Trainers who can work with us part - time with the following skills: Experience using statistical computer languages (R, Python etc.) to manipulate data and draw insights from large data sets. Should have strong programming & Good applied statistics skills, such as distributions, statistical testing, regression, etc. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.Few examples are k-NN, Naive Bayes, SVM, Decision Forests,Random Forest ,Support vector machine,Principal component analysis. Experience using natural language processing techniques and Deep Learning using TensorFlow will be a plus. Should have minimum 5 years of relevant work experience.