This is a magic property of Poisson processes.
Let $\mu = 2$ and $\lambda = 3$ be the rates of your two machines
Now I want to know the probability that I get nothing out of either machine in the first $t$ minutes.
I get nothing out of machine $A$ with probaiblity $e^{-\mu t}$ and nothing out of machine $B$ with probability $e^{-\lambda t}$.
So as the machines are independent I get nothing out of the either machine with probability $e^{-(\mu+\lambda)t}$.
So the two machines working together act like a Poisson machine producing at a rate of $5$ per minute.
You should be able to recognise the distribution of the waiting time above and calculate the mean.
Now lets try a similar approach for the question you actually asked so that I can pretend that was a warm up exercise and not just idiot boy here not reading the question.
We already know that the first product comes out of the machine after an exponential waiting time mean $\frac 15$ and variance $\frac 1{25}$.
So the amount of time I have to wait before I get two is the sum of two independent exponentials, hence has mean $\frac 25$ and variance $\frac 2{25}$.
So how many pairs do I need to see before I get a package with one from each?
For a fixed time $t$ the probability I've seen one product from $A$ and none from $B$ is $e^{-(\lambda+\mu)} \frac \mu{0!\cdot 1!}$ and the probability I've seen one from $B$ and none from $A$ is $e^{-(\lambda+\mu)} \frac \lambda{0!\cdot 1!}$ so conditioned on the event only one product has been seen the probability it came from $A$ is $\frac{\mu}{\mu+\lambda}$ or $\frac 25$.
Now the output of the machines is independent and memoryless so the sequence of products is an iid sequence. Therefore the probability the firs pair gives a proper package is $2\cdot \frac 25\cdot\frac 35 = \frac{12}{25}$.
Let $N$ be the number of packages we make before we get a good one. (So the $N$th package is good) We have
$$P(N = n) = \left(\frac {13}{25}\right)^{n-1}\left(\frac {12}{25}\right)$$
Now the packages arrive at independent intervals of length $T_i$ each of which has $E(T) = \frac 15$ and $E(T^2) = \frac 2{25}$ so with total Waiting time
$$T = \sum_{i=1}^N T_i$$
So if I know $N$ I can write
$$E(T|N) = NE(T_i) = \frac N5$$and
$$E(T^2|N) = \left(\sum_{i=1}^N T_i\right)^2 = \sum_{i=1}^N E(T_i)^2 + 2\sum_{i\neq j} E(T_i)E(T_j)$$ $$= NE(T_i^2) + (N^2-N)E(T_i)^2 = \frac{N^2 + N}{25}$$
You get to take it from here. You know the distribution of $N$ so you can work out $E(T) = \frac{E(N)}5$ and $E(T^2) = \frac{E(N^2+N)}{25}$ So you should be able to get the mean and variance.